<p>A global law firm in the Twin Cities seeks a <strong>detail-oriented Patent Agent</strong> with proven experience in patent prosecution. This position offers direct collaboration with inventors and attorneys on <strong>cutting-edge technologies</strong> to secure and protect valuable intellectual property. If you are passionate about innovation, this is an excellent opportunity.</p><p><br></p><p>Responsibilities:</p><p>• Collaborate with inventors and researchers to assess the patentability of innovative technologies.</p><p>• Draft, file, and prosecute patent applications with a focus on wireless technologies, artificial intelligence (AI), and processor and memory systems.</p><p>• Respond to United States Patent and Trademark Office (USPTO) actions effectively and in a timely manner.</p><p>• Maintain and manage patent portfolios for clients, ensuring alignment with their strategic objectives.</p><p>• Stay informed about advancements in 5G, Wi-Fi, and other wireless technologies, as well as AI and related fields.</p><p>• Provide expert guidance to clients regarding intellectual property strategies and best practices.</p><p>• Conduct in-depth research on prior art to support patent applications and strengthen intellectual property claims.</p><p>• Engage in client meetings to understand their needs and provide tailored solutions.</p><p>• Ensure compliance with legal and regulatory requirements throughout the patent prosecution process.</p>
<p>We’re hiring a hands-on Staff Software Engineer to lead development in a critical area of AI-enabled product infrastructure. In this role, you will build and evolve the systems that determine what AI-powered experiences can access, use, and reference in real time. This work is central to ensuring outputs are accurate, timely, secure, and grounded in the right information.</p><p><br></p><p>You will focus on designing and improving retrieval and context systems that support intelligent applications operating in complex, high-trust environments. That includes helping systems identify the right content, manage changing information, and enforce strict access boundaries. You’ll work primarily in Python and collaborate closely with cross-functional partners in product, data, and engineering.</p><p>This is a highly hands-on role for someone who wants to directly influence the architecture, quality, and safety of AI-driven capabilities.</p><p><br></p><p>What You’ll Do</p><ul><li>Lead the design and improvement of retrieval systems that support AI-powered workflows in production environments</li><li>Ensure application outputs are grounded in the right source material, with the appropriate balance of quality, performance, and cost</li><li>Build systems that can process and reason over large volumes of unstructured and structured content</li><li>Develop search and context tools that surface trustworthy source excerpts, references, and relevant content locations</li><li>Maintain alignment between what AI systems can access and what end users are authorized to view</li><li>Help define when AI-generated outputs can be delivered directly and when additional validation or product controls are required</li><li>Influence technical direction across teams and mentor engineers working in adjacent problem spaces</li></ul><p><br></p>
Talent Sourcer | Help Build the Future of Enterprise AI San Mateo, CA | Hybrid/Onsite | Contract or Contract-to-permanent <br> Join an AI Company Transforming What's Possible! <br> Robert Half is partnering with a rapidly growing AI technology company that is helping organizations build, train, and deploy next-generation artificial intelligence solutions. Backed by industry-leading investors and founded by pioneers in AI infrastructure, our client is shaping the future of enterprise AI through cutting-edge technology, innovation, and world-class talent. As the company continues to scale, they are seeking a strategic and driven Talent Sourcer to play a key role in identifying and engaging exceptional talent across both technical and go-to-market functions. This is an opportunity to join a high-growth environment where your ability to build pipelines, uncover hard-to-find talent, and influence hiring outcomes will have a direct impact on the organization's success. <br> Position Description: <br> The Talent Sourcer will serve as a critical partner to the Talent Acquisition team, helping build and maintain strong candidate pipelines for priority hiring initiatives. This individual will proactively identify, engage, and attract top talent while leveraging market intelligence and sourcing best practices to support hiring across engineering, AI, infrastructure, and business functions. <br> Responsibilities: <br> Proactively source and engage passive candidates through LinkedIn Recruiter, GitHub, technical communities, open-source networks, and other creative sourcing channels. Build and maintain robust talent pipelines across technical and go-to-market roles. Partner closely with recruiters, hiring managers, and business leaders to understand hiring needs and develop targeted sourcing strategies. Create compelling, personalized outreach campaigns that effectively communicate the company's mission, culture, and career opportunities. Conduct initial candidate conversations to assess qualifications, experience, and overall alignment with hiring requirements. Research competitor organizations, emerging talent pools, and industry trends to inform sourcing strategies and hiring decisions. Support diversity hiring initiatives by building inclusive candidate pipelines and implementing equitable sourcing practices. Maintain accurate candidate records and sourcing activity within the Applicant Tracking System (ATS). Monitor sourcing metrics, pipeline health, and conversion data to identify opportunities for process improvement. Continuously explore new sourcing tools, technologies, and engagement strategies to improve recruiting outcomes.
<p><strong>Software Engineer, AI</strong></p><p><br></p><p><strong>Company Overview</strong> </p><p>A growing organization is seeking an AI Engineer to develop automation, data, and AI-driven solutions that improve business processes and operational efficiency. This role offers the opportunity to work on innovative projects while helping shape the organization's use of emerging technologies.</p><p><br></p><p><strong>Role Summary</strong> </p><p>The AI Engineer will design, build, and support AI-powered applications, automation solutions, and data-driven workflows. The ideal candidate combines strong software engineering skills with experience delivering practical AI solutions in a business environment.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, develop, and support AI-enabled applications and automation solutions.</li><li>Partner with business and technical teams to identify opportunities for process improvement.</li><li>Build integrations between AI solutions, data sources, and business applications.</li><li>Monitor solution performance and continuously improve reliability and effectiveness.</li><li>Develop and maintain technical documentation and best practices.</li><li>Support the evaluation and adoption of emerging AI technologies.</li></ul>
<p><strong>Data Pipeline Development & Integration</strong></p><ul><li>Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from multiple sources.</li><li>Develop automated data integration solutions supporting enterprise applications, analytics, and reporting.</li><li>Integrate structured and semi-structured data from APIs, relational databases, cloud platforms, and third-party systems.</li><li>Develop batch and real-time data processing solutions.</li><li>Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.</li></ul><p><strong>Data Warehousing & Architecture</strong></p><ul><li>Design and optimize enterprise data warehouses, data lakes, and lakehouse architectures.</li><li>Develop efficient data models, schemas, and transformations to support business intelligence and analytics.</li><li>Build and maintain cloud-based data solutions using AWS, Microsoft Azure, or Google Cloud.</li><li>Optimize SQL queries, database performance, and data processing workloads.</li><li>Implement data partitioning, indexing, and storage optimization strategies.</li></ul><p><strong>Data Quality & Governance</strong></p><ul><li>Develop automated data validation, monitoring, and quality assurance processes.</li><li>Ensure data accuracy, consistency, reliability, and availability across enterprise systems.</li><li>Implement data governance standards, access controls, and security best practices.</li><li>Maintain documentation for data pipelines, architecture, and transformation logic.</li><li>Support compliance with organizational data privacy and security requirements.</li></ul><p><strong>Cloud Engineering & Automation</strong></p><ul><li>Develop and maintain cloud-native data pipelines and processing workflows.</li><li>Utilize orchestration tools such as Apache Airflow, Azure Data Factory, or similar technologies.</li><li>Implement CI/CD practices for data engineering workflows.</li><li>Automate data processing, monitoring, and infrastructure deployment.</li><li>Collaborate with DevOps and infrastructure teams to improve scalability and reliability.</li></ul><p><strong>Analytics & AI Support</strong></p><ul><li>Partner with business intelligence and analytics teams to deliver reliable datasets for reporting and dashboards.</li><li>Develop curated data models supporting Power BI, Tableau, and other visualization platforms.</li><li>Build data pipelines supporting machine learning, predictive analytics, and AI applications.</li><li>Collaborate with AI engineers and data scientists to prepare, transform, and deliver data for model development and production applications.</li><li>Identify opportunities to improve business processes through better data integration and automation.</li></ul><p><br></p><p><br></p>
<p><strong>Data Pipeline Development & Integration</strong></p><ul><li>Design, build, and maintain scalable ETL/ELT pipelines to extract, transform, and load data from multiple sources.</li><li>Develop automated data integration solutions supporting enterprise applications, analytics, and reporting.</li><li>Integrate structured and semi-structured data from APIs, relational databases, cloud platforms, and third-party systems.</li><li>Develop batch and real-time data processing solutions.</li><li>Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks.</li></ul><p><strong>Data Warehousing & Architecture</strong></p><ul><li>Design and optimize enterprise data warehouses, data lakes, and lakehouse architectures.</li><li>Develop efficient data models, schemas, and transformations to support business intelligence and analytics.</li><li>Build and maintain cloud-based data solutions using AWS, Microsoft Azure, or Google Cloud.</li><li>Optimize SQL queries, database performance, and data processing workloads.</li><li>Implement data partitioning, indexing, and storage optimization strategies.</li></ul><p><strong>Data Quality & Governance</strong></p><ul><li>Develop automated data validation, monitoring, and quality assurance processes.</li><li>Ensure data accuracy, consistency, reliability, and availability across enterprise systems.</li><li>Implement data governance standards, access controls, and security best practices.</li><li>Maintain documentation for data pipelines, architecture, and transformation logic.</li><li>Support compliance with organizational data privacy and security requirements.</li></ul><p><strong>Cloud Engineering & Automation</strong></p><ul><li>Develop and maintain cloud-native data pipelines and processing workflows.</li><li>Utilize orchestration tools such as Apache Airflow, Azure Data Factory, or similar technologies.</li><li>Implement CI/CD practices for data engineering workflows.</li><li>Automate data processing, monitoring, and infrastructure deployment.</li><li>Collaborate with DevOps and infrastructure teams to improve scalability and reliability.</li></ul><p><strong>Analytics & AI Support</strong></p><ul><li>Partner with business intelligence and analytics teams to deliver reliable datasets for reporting and dashboards.</li><li>Develop curated data models supporting Power BI, Tableau, and other visualization platforms.</li><li>Build data pipelines supporting machine learning, predictive analytics, and AI applications.</li><li>Collaborate with AI engineers and data scientists to prepare, transform, and deliver data for model development and production applications.</li><li>Identify opportunities to improve business processes through better data integration and automation.</li></ul><p><br></p><p><br></p>
<p>We are looking for a skilled AI Software Engineer to join our team in Phoenix, Arizona. In this long-term contract role. We want a full-stack software engineer who ships at AI speed without giving up engineering judgment. You'll use AI coding agents as your main tool, and you'll be the person who knows when the agent is wrong.</p><p><br></p><p>Responsibilities:</p><p>· <strong>Build department workspaces end to end.</strong> Ticket hubs, queues, tiles and filters for Client Services, Legal, HR and Compliance (e.g. a ClickUp-style filter builder, a performance-review system, a legal case tracker).</p><p>· <strong>Work on regulated workflows.</strong> Credit-dispute (e-OSCAR ACDV) queues with locking, auto-submit and audit trails, where a bug means a compliance issue, not just a broken screen.</p><p>· <strong>Replace CollectOne, one department at a time.</strong> Read legacy SQL Server data, mirror it into Postgres, and rebuild the daily screens staff rely on.</p><p>· <strong>Write database migrations safely.</strong> Plan apply-before-merge order, row-level security, and one-transaction-per-page-load rules.</p><p>· <strong>Wire integrations.</strong> Microsoft Graph mailboxes into tickets, Amazon Connect call screens, AWS Bedrock AI features (reply suggestions, PDF invoice analysis), S3 uploads, Stripe and QuickBooks.</p><p>· <strong>Drive AI agents well.</strong> Write clear prompts and specs, break work into small stacked PRs, and review every line the agent writes.</p><p>· <strong>Keep CI honest.</strong> Respect the guard checks (page index, lint ratchet, migration hygiene, secret scanning) and add new guards when a mistake could repeat.</p><p>· <strong>Sit with users.</strong> Turn a messy request from a supervisor into a clear spec, then show them the working screen.</p>
<p>Robert Half is partnering with a rapidly growing, industry-leading AI company that is transforming how businesses build, train, and deploy artificial intelligence. Backed by leading venture capital firms and technology innovators, this organization is at the forefront of enterprise AI and is continuing to scale its world-class team.</p><p><br></p><p>We are seeking a driven, strategic <strong>GTM Recruiter</strong> for a contract-to-hire opportunity to help fuel the company's next phase of growth. This is an exciting opportunity for a recruiter who thrives in a fast-paced environment, enjoys partnering with senior business leaders, and is passionate about leveraging AI to modernize the talent acquisition process.</p><p>In this role, you will lead full-cycle recruiting across Go-to-Market functions, including Sales, Marketing, Partnerships, Solutions Engineering, and Customer Success. You'll work closely with hiring managers and executive stakeholders to develop effective hiring strategies, build strong talent pipelines, and attract exceptional candidates who will help bring innovative AI solutions to market.</p><p><br></p><p>The ideal candidate combines strong recruiting fundamentals with a proactive sourcing mindset, a passion for emerging technology, and a willingness to experiment with AI-powered recruiting tools to improve efficiency and candidate engagement.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Manage full-cycle recruiting for GTM positions across Sales, Marketing, Partnerships, Solutions Engineering, and Customer Success.</li><li>Partner with hiring managers and senior leadership to define role requirements, align on candidate profiles, and develop targeted recruiting strategies.</li><li>Proactively source, engage, and build relationships with high-caliber candidates through direct outreach, referrals, networking, and AI-powered sourcing platforms.</li><li>Develop and maintain talent pipelines and market maps to support immediate hiring needs and future workforce growth.</li><li>Collaborate with People team partners, including HR Business Partners and Compensation, to support role development, compensation benchmarking, and hiring plans.</li><li>Leverage AI-driven recruiting tools, sourcing automation, and personalized outreach strategies to improve recruiting efficiency and candidate engagement.</li><li>Monitor pipeline activity, recruiting metrics, and hiring progress to identify opportunities to improve processes and deliver results.</li><li>Deliver a high-quality candidate experience while balancing speed, hiring priorities, and quality of hire.</li><li>Contribute to the development of scalable, inclusive recruiting processes and innovative talent acquisition practices.</li></ul><p><br></p>
<p><strong>Senior Software Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading firm based in Los Angeles, California is seeking a Senior Software Engineer to join its technology organization. The firm manages a significant portfolio of institutional assets across credit, private investments, and other alternative strategies. Technology and AI are central to its ongoing innovation strategy, with continued investment in intelligent applications, automation, and data-driven solutions.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Senior Software Engineer will be a hands-on full-stack developer responsible for building and supporting internal applications, AI-enabled solutions, enterprise integrations, and the Salesforce platform. This role will work closely with investment, operations, compliance, investor relations, accounting, and data teams to turn complex business processes into scalable technology solutions. </p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design and develop applications that automate workflows across investment management, compliance, operations, accounting, and investor relations.</li><li>Build full-stack solutions using C#, .NET, SQL, Python, JavaScript/TypeScript, APIs, and modern development frameworks.</li><li>Develop and support AI-enabled applications, agent workflows, document processing, and intelligent automation solutions.</li><li>Configure and enhance Salesforce, including objects, fields, flows, validation rules, security, integrations, and light custom development.</li><li>Build integrations between Salesforce, internal applications, data platforms, and third-party systems using APIs, ETL, messaging, and automation.</li><li>Develop data and document processing workflows that extract, validate, transform, and load information into enterprise systems.</li><li>Partner directly with investment and business teams to translate domain expertise into repeatable, automated workflows.</li><li>Support reporting and analytics initiatives while maintaining data quality and consistency across connected systems.</li><li>Troubleshoot production applications and integrations, perform root-cause analysis, and implement long-term solutions.</li><li>Apply AI-assisted engineering practices to accelerate development, testing, documentation, and process automation.</li></ul><p><strong>Additional Details</strong></p><ul><li>Work model: Hybrid, three days onsite per week</li><li>Quarterly travel may be required</li><li>Opportunity to join an organization with an established investment in AI and help build the next generation of internal AI capabilities</li><li>Direct collaboration with senior technology leadership and investment professionals</li></ul>
Position: Data Engineer<br>Location: Oskaloosa, IA / Des Moines, IA -- Onsite<br>Salary: $100,000 - $120,000 base + exceptional benefits<br><br>*** For immediate and confidential consideration, please APPLY and EMAIL YOUR RESUME to MEREDITH CARLE . My email can be found on my LinkedIn page. ***<br><br>Data Engineer<br>Shape the Future of Enterprise Analytics, AI & Data Innovation<br>Are you the type of data professional who sees a business problem and immediately starts thinking about how to model, engineer, and deliver the right solution?<br>A highly successful, technology-driven organization is seeking a Data Engineer to help build the foundation for enterprise analytics, business intelligence, governance, and next-generation AI initiatives. This is an opportunity to make a visible impact across the business while working alongside a collaborative team of data professionals who are passionate about solving complex challenges.<br>This role is ideal for someone who enjoys being hands-on, partnering with the business, and building modern data solutions that drive meaningful outcomes.<br>What You'll Do<br> • Design and develop scalable data models, semantic layers, and enterprise data solutions<br> • Build trusted data structures that support analytics, reporting, AI, and business intelligence initiatives<br> • Develop and optimize cloud-based data pipelines and integrations<br> • Improve data governance, lineage, metadata management, and observability practices<br> • Create automated data quality and validation frameworks<br> • Implement CI/CD processes and modern DataOps best practices<br> • Optimize SQL performance across warehouses, lakehouses, and reporting environments<br> • Partner with analysts and business stakeholders to transform complex problems into actionable solutions<br> • Contribute to technical standards, mentoring, documentation, and architectural best practices<br>What We're Looking For<br>Core Qualifications<br> • Strong experience with data modeling and semantic modeling<br> • Hands-on experience with Microsoft Fabric, Azure, and Power BI<br> • Advanced SQL development and performance optimization skills<br> • Experience with Git, CI/CD, and modern data engineering practices<br> • Ability to translate business requirements into scalable technical solutions<br> • Experience developing enterprise data pipelines and analytics platforms<br> • A plus if you have data governance, data warehouse, data lake and or DBT experience.<br><br>*** For immediate and confidential consideration, please APPLY and EMAIL YOUR RESUME to MEREDITH CARLE . My email can be found on my LinkedIn page. Also, you may contact me at 515-303-4654. Or one click apply on our Robert Half website. No third party inquiries please. Our client cannot provide sponsorship and cannot hire C2C. ***
GTM Recruiter (Contract-to-permanent) About the Opportunity Our recruiting team is partnering with a rapidly growing AI company at the forefront of building innovative artificial intelligence solutions for enterprise customers. As the company continues to scale, they are seeking a motivated GTM Recruiter to support hiring across key revenue-generating functions and help build a world-class team. Position Description Lead full-cycle recruiting for Go-to-Market (GTM) roles, including Sales, Marketing, Partnerships, Solutions Engineering, and Customer Success Partner closely with hiring managers and business leaders to understand hiring needs and develop recruiting strategies Source, engage, and attract top talent through networking, referrals, direct outreach, and recruiting tools Build and maintain strong candidate pipelines to support both current and future hiring initiatives Utilize AI-driven sourcing and recruiting technologies to improve efficiency and candidate engagement Manage multiple requisitions while delivering a positive candidate experience throughout the hiring process Track recruiting activity, pipeline metrics, and hiring progress to ensure timely results Collaborate with HR and cross-functional stakeholders to support workforce planning and hiring goals Contribute to scalable recruiting processes and best practices as the organization continues to grow
<p>We’re seeking a Staff Software Engineer to lead technical strategy and execution across a product domain or platform area spanning multiple teams. In this role, you will own outcomes end-to-end by defining success metrics, shaping the roadmap, and driving measurable improvements over time.</p><p><br></p><p>You will set the architectural direction for scalable APIs, backend services, data platforms, and event-driven systems that operate across team boundaries. You’ll also lead the most complex work related to performance, scalability, and reliability.</p><p>As a senior technical leader, you will raise the engineering bar across the organization by establishing standards, creating reusable platforms and patterns, improving documentation practices, simplifying systems, and reducing technical debt.</p><p>You’ll be responsible for making and communicating high-impact technical decisions across architecture, security, performance, cost, and scalability. This includes identifying risks early and designing safeguards before they become incidents.</p><p>This role requires close partnership with Product, Design, Machine Learning, Client Success, and engineering leadership to shape strategy, turn ambiguous business goals into clear multi-quarter technical plans, and align teams on execution.</p><p>You will also help define how the organization adopts AI-assisted and agentic development practices by establishing guardrails for verification, security, and human accountability in production decisions, while measuring the real impact these tools create.</p><p>In addition, you will mentor senior engineers, influence technical direction across the organization, lead architecture reviews, and remain hands-on with the highest-impact technical work.</p><p><br></p>
<p><strong>Machine Learning Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>Based in Los Angeles, California, the company specializes in transforming complex, multi-source data into actionable insights through machine learning, knowledge graph technologies, and advanced analytics. This is an opportunity to work on mission-critical applications in a highly collaborative environment focused on innovation, scalability, and operational excellence.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Machine Learning Engineer will play a critical role in designing, training, deploying, and optimizing machine learning models that operate on large-scale temporal, geospatial, relational, and unstructured datasets. </p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design, train, evaluate, deploy, and optimize machine learning models across multiple production use cases.</li><li>Build predictive solutions for anomaly detection, forecasting, entity resolution, relationship prediction, risk assessment, and operational decision support.</li><li>Partner with data engineering teams to develop high-quality training datasets from structured, unstructured, temporal, relational, and geospatial data sources.</li><li>Design model architectures and select appropriate algorithms based on business objectives, data characteristics, and operational requirements.</li><li>Develop and maintain machine learning pipelines spanning data preparation, feature engineering, training, evaluation, deployment, and monitoring.</li><li>Build scalable solutions that leverage graph-based and knowledge graph-driven data architectures.</li><li>Establish rigorous evaluation frameworks, baselines, performance metrics, and validation methodologies.</li><li>Design experiments that mitigate data leakage, model drift, bias, and changing data distributions.</li><li>Implement monitoring, observability, alerting, retraining, rollback, and model governance processes.</li><li>Maintain reproducible datasets, model artifacts, evaluation results, and deployment workflows.</li><li>Collaborate with distributed engineering teams to deliver reliable and scalable machine learning capabilities.</li><li>Improve model calibration, confidence scoring, uncertainty estimation, and explainability.</li><li>Contribute to technical architecture, machine learning standards, and long-term platform strategy.</li></ul>
We are looking for a Senior Data Engineer to strengthen our data foundation and help deliver reliable, scalable information solutions across Minneapolis, Minnesota. In this role, you will create and optimize modern data platforms that power analytics, reporting, and machine learning initiatives. You will collaborate with technical and business partners to turn complex source data into trusted, accessible assets that support better decisions across the organization.<br><br>Responsibilities:<br>• Build and maintain scalable data pipelines that ingest, transform, and deliver information from a variety of enterprise and operational data sources.<br>• Design data models and warehouse structures that improve reporting performance, support analytics use cases, and enable long-term scalability.<br>• Develop and orchestrate ETL and ELT workflows using cloud-based and workflow automation tools to ensure dependable data movement across systems.<br>• Create batch and near-real-time processing solutions that provide timely, accurate datasets for downstream applications and analytical teams.<br>• Write efficient, well-structured Python and SQL code to cleanse, transform, and validate large and complex datasets.<br>• Monitor pipeline health, investigate failures, and tune jobs for reliability, cost control, and overall platform performance.<br>• Establish data quality checks, testing routines, and governance practices to maintain consistency, integrity, and compliance across the data environment.<br>• Partner with architects, analysts, data scientists, AI/ML engineers, and DevOps teams to support production-ready data products, automated deployments, and reproducible machine learning workflows.
We are seeking a highly skilled Big Data Engineer to design, build, and optimize scalable data platforms that support enterprise analytics, reporting, machine learning, and business intelligence initiatives. The ideal candidate will have experience developing large-scale data pipelines, managing cloud-based data ecosystems, and implementing high-performance data solutions that enable data-driven decision-making across the organization. Key Responsibilities Design, develop, and maintain large-scale data processing systems and data pipelines. Build and optimize ETL/ELT workflows for structured, semi-structured, and unstructured data sources. Develop scalable solutions using distributed computing frameworks such as Apache Spark, Hadoop, and Kafka. Collaborate with Data Scientists, Analysts, Architects, and business stakeholders to support analytical and operational requirements. Integrate data from multiple internal and external systems while ensuring data quality and integrity. Design and implement cloud-native data solutions within AWS, Azure, or Google Cloud environments. Monitor, troubleshoot, and improve the performance, reliability, and scalability of data platforms. Implement data governance, security, compliance, and access control standards. Support real-time and batch data processing requirements. Document architectures, workflows, and technical specifications to ensure operational excellence.
<p><strong>Software Engineer</strong></p><p><br></p><p><strong>Company Overview</strong></p><p>A leading organization is seeking a Software Engineer to help develop next-generation AI platforms. This is an opportunity to work on cutting-edge AI technologies within a highly collaborative and innovative engineering environment.</p><p><br></p><p><strong>Role Summary</strong></p><p>The Software Engineer will design, build, and optimize enterprise-grade AI platforms that connect structured and unstructured data, knowledge graphs, retrieval systems, and intelligent workflows. The ideal candidate combines strong software engineering fundamentals with expertise in AI systems, distributed architectures, and scalable platform development.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design and implement intelligent workflow systems for research, analysis, automation, and decision-support use cases.</li><li>Develop scalable retrieval, search, and knowledge management capabilities across structured and unstructured datasets.</li><li>Build backend services, APIs, and platform capabilities supporting AI-driven applications.</li><li>Create resilient workflow orchestration patterns for long-running, distributed, and fault-tolerant processes.</li><li>Develop authorization, permission management, auditing, and governance mechanisms within AI platforms.</li><li>Optimize retrieval, inference, and execution performance across diverse deployment environments.</li><li>Fine-tune, evaluate, and integrate open-source AI models to support specialized business workflows.</li><li>Implement model routing, inference optimization, caching, and fallback strategies.</li><li>Build evaluation frameworks that measure system accuracy, reliability, performance, and operational effectiveness.</li><li>Develop observability, monitoring, alerting, and troubleshooting capabilities across platform components.</li><li>Partner with product, data, machine learning, infrastructure, security, and customer-facing teams to deliver scalable solutions.</li><li>Contribute to technical architecture, engineering standards, and long-term platform strategy.</li></ul>
<p>We are seeking a <strong>Senior Data Engineer</strong> to join a growing data and analytics team responsible for building modern, cloud-based data platforms that drive business intelligence, reporting, and advanced analytics. This role is ideal for someone with deep expertise in <strong>Microsoft Azure</strong>, <strong>Microsoft Fabric</strong>, and modern data engineering practices.</p><p>You will be responsible for designing and developing scalable data solutions, optimizing data pipelines, and helping shape the organization's data architecture strategy. The ideal candidate is both hands-on and strategic, with experience building enterprise data platforms in Azure and Fabric environments.</p><p>Responsibilities</p><ul><li>Design, develop, and maintain enterprise data solutions using <strong>Microsoft Fabric</strong> and <strong>Azure Data Services</strong>.</li><li>Build and optimize scalable ETL/ELT pipelines for structured and unstructured data sources.</li><li>Develop and manage data lakes, lakehouses, warehouses, and semantic models.</li><li>Design data integration solutions using Fabric Data Factory, Dataflows, and Azure Data Factory.</li><li>Implement data governance, security, quality, and monitoring frameworks.</li><li>Partner with business stakeholders to understand reporting and analytics requirements.</li><li>Support Power BI developers by building trusted, high-quality data models and datasets.</li><li>Optimize data storage, query performance, and platform scalability.</li><li>Develop data architecture standards, best practices, and documentation.</li><li>Collaborate with application development teams to integrate operational systems with enterprise analytics platforms.</li><li>Support real-time and batch data processing initiatives.</li><li>Participate in architecture reviews, code reviews, and technical leadership activities.</li></ul><p><br></p>
We are looking for an Applied AI Training Engineer to join a Contract opportunity in San Francisco, California. This role focuses on shaping high-quality data and evaluation assets that strengthen how large language models learn specialized enterprise software concepts, workflows, and decision patterns. The ideal candidate will combine AI training expertise, strong technical judgment, and close collaboration with subject matter experts to improve model accuracy, consistency, and real-world usefulness across complex business scenarios.<br><br>Responsibilities:<br>• Develop structured training examples that help large language models learn enterprise software behaviors, terminology, and task flows with precision.<br>• Collaborate with subject matter experts to convert product knowledge, process logic, and business context into usable datasets for model training.<br>• Define data design approaches that expand domain coverage and support reliable model performance across a wide range of user scenarios.<br>• Build, organize, and enhance large-scale datasets, including generating synthetic examples when they add value to model learning.<br>• Review model responses, investigate failure patterns, and adjust training content to close knowledge gaps and improve output quality.<br>• Establish reusable frameworks, taxonomies, and teaching methods for introducing new concepts, schemas, and specialized domains to AI systems.<br>• Create benchmark datasets and evaluation methods to measure reasoning quality, factual accuracy, coverage, and generalization.<br>• Implement quality controls that detect inconsistency, ambiguity, imbalance, and missing information within training data collections.<br>• Write and maintain Python-based tools to create, transform, validate, and manage training data efficiently at scale.<br>• Refine model behavior to better align responses with customer expectations, domain expertise, and intended software functionality.
<p>Robert Half is hiring! We are looking for a Principal Software Engineer to lead the design and delivery of modern AI-driven software solutions. This role combines hands-on engineering with technical leadership across backend services, frontend applications, and intelligent workflow development. The ideal candidate brings deep full-stack expertise, a strong product mindset, and the ability to guide scalable systems from concept through production.</p><p><br></p><p>Responsibilities:</p><p>• Lead complete product delivery efforts, from technical planning and architecture through implementation, testing, and long-term support.</p><p>• Create and refine agentic AI workflows that support business goals and integrate effectively with broader application ecosystems.</p><p>• Build, enhance, and support scalable server-side applications using Python frameworks such as Django, Flask, or FastAPI, or Node.js frameworks including Express or NestJS.</p><p>• Develop robust RESTful and GraphQL interfaces that enable reliable communication between platforms, services, and user-facing applications.</p><p>• Implement and improve React-based frontend features with a focus on usability, responsiveness, and smooth integration with backend systems.</p><p>• Architect and maintain microservices and distributed application components to support performance, resilience, and future growth.</p><p>• Improve system efficiency by tuning application behavior, streamlining database interactions, and optimizing cloud infrastructure usage.</p><p>• Apply strong security standards by implementing access controls, authentication mechanisms, and authorization practices across the platform.</p><p>• Oversee automated delivery processes and container-based deployments using CI/CD pipelines, Docker, and related engineering tools.</p><p>• Partner with product, design, and DevOps teams to resolve production issues, maintain cloud-based services, and deliver high-quality software outcomes.</p>
Transform the Future of AI, Analytics & Intelligent Automation <br> We are seeking a highly innovative Director of Data Science & Analytics to lead the next evolution of an enterprise's analytics and AI capabilities. This leadership opportunity will oversee Business Intelligence, Data Science, and emerging AI-focused engineering functions while helping shape the company's long-term data and AI strategy. This role is ideal for somebody who thrives at the intersection of business strategy, technology, and talent development. You'll have the opportunity to build and scale high-performing teams, influence executive decision-making, and drive meaningful business outcomes through advanced analytics, machine learning, and AI-enabled solutions. <br> Responsibilities: • Define and advance the enterprise vision for analytics and AI in partnership with senior leadership, balancing immediate business needs with long-range capability building. • Help experienced the organization's approach to AI adoption, intelligent workflows, and advanced decision support capabilities. • Direct and develop managers and technical teams across business intelligence, data science, and applied engineering functions embedded within cross-functional operating groups. • Expand the use of machine learning, forecasting, optimization, and advanced analytical methods to solve business problems and generate measurable value. • Elevate reporting and analytics practices by improving semantic layers, strengthening data trust, and enabling effective self-service access for business users. • Build and scale a team focused on delivering end-to-end AI applications, including generative AI and agent-based solutions. • Partner with leaders across commercial, operations, product, and corporate areas to prioritize initiatives, align resources, and guide investment decisions. • Establish governance for model development, MLOps, validation practices, reusable code assets, and quality standards across analytics delivery. • Help shape platform direction and solution delivery across environments such as Azure and Databricks while supporting scalable analytics architecture. • Lead organizational planning efforts including hiring strategy, succession planning, team design, and capability development as the function grows. • Foster a high-accountability culture that encourages experimentation, rapid learning, continuous improvement, and strong ownership of outcomes.
<p>We are looking for a senior Data Engineer. This position combines architectural leadership with hands-on development across a modern cloud data ecosystem, with a strong focus on building dependable, scalable, and efficient data solutions. The role will help shape engineering standards, strengthen platform governance, and support high-quality data delivery for enterprise analytics and emerging AI-driven use cases.</p><p><br></p><p>Responsibilities:</p><p>• Provide technical direction to engineering teams and guide the successful execution of complex data platform initiatives.</p><p>• Create and enhance robust data pipelines and reusable data products that support scalable analytics and reporting needs.</p><p>• Develop and refine cloud-based data solutions using Snowflake, dbt, Fivetran, and Azure services.</p><p>• Build automation-first, metadata-driven processing frameworks to improve consistency, maintainability, and operational efficiency.</p><p>• Design curated data structures using established modeling approaches such as Data Vault, Kimball, and dimensional modeling.</p><p>• Improve platform performance through tuning, cost management, and scalability planning across data workloads.</p><p>• Establish and reinforce best practices for data quality, governance, lineage tracking, observability, and CI/CD delivery.</p><p>• Support Azure-based integration, storage, compute, and DevOps capabilities required for reliable end-to-end data operations.</p><p>• Enable data foundations that can support advanced analytics, AI/ML initiatives, and modern analytical architectures.</p>
We are looking for a Computer Vision Engineer to join a growing team building AI-driven solutions for manufacturing environments in Cambridge, Massachusetts. In this role, you will create and deploy vision models that interpret live camera feeds to support defect detection and workflow monitoring across industrial settings. This position is ideal for an engineer who enjoys turning machine learning concepts into reliable production systems and collaborating closely with technical teams to deliver measurable operational value.<br><br>Responsibilities:<br>• Design, train, and refine computer vision models for manufacturing use cases such as defect identification, anomaly detection, and step-by-step task tracking.<br>• Build production-ready Python-based machine learning pipelines using frameworks such as PyTorch or TensorFlow.<br>• Work with image and video data captured from facility cameras to develop accurate and scalable real-time analysis solutions.<br>• Deploy and support vision applications in cloud and edge environments, including AWS services such as S3 and EC2.<br>• Collaborate with engineering leadership and cross-functional teammates to translate customer needs into practical model and system designs.<br>• Create solutions from the ground up using supervised and unsupervised learning techniques where appropriate.<br>• Improve system performance through testing, evaluation, and iterative tuning of algorithms in live operational settings.<br>• Participate in periodic onsite visits to customer facilities to understand workflows, validate model behavior, and support implementation.
One of Robert Half's clients is looking for a curious, resourceful Data Platform Engineer to help us strengthen the foundation behind our data. This is a hands-on, growth-oriented role for someone who enjoys investigating how systems work, solving practical problems, and learning new technologies. You will help build and maintain data pipelines, improve the reliability and accessibility of our data, and contribute to an assessment of our current data architecture. <br><br>You will have the opportunity to work across several areas of data engineering rather than being limited to one narrow specialty. This may include data integration, pipeline development, data modeling, quality monitoring, documentation, reporting support, and architecture discovery. We are more interested in how you approach problems than whether you have already used every technology in our environment. The right person is dependable, asks thoughtful questions, follows work through to completion, and knows how to use modern AI development tools responsibly and effectively. <br><br>Essential Functions <br><br>Build, maintain, and improve pipelines that move data between operational systems, databases, warehouses, and reporting tools. <br><br>Help document our existing data environment, including data sources, integrations, transformations, storage, reporting dependencies, and access controls. <br><br>Support an audit of the current data architecture by investigating how systems connect and identifying potential reliability, scalability, data-quality, security, or maintainability concerns. <br><br>Work with more experienced team members and business stakeholders to evaluate and prioritize improvements. <br><br>Develop and maintain reusable data models for reporting, analytics, and operational use. <br><br>Add testing, monitoring, alerting, logging, and documentation to important data workflows. <br><br>Investigate failed jobs, inconsistent metrics, and other data issues through structured root-cause analysis. <br><br>Write readable, maintainable code using source control, code review, automated testing, and repeatable deployment practices. <br><br>Translate business needs into practical technical solutions with guidance from internal stakeholders. <br><br>Use AI-assisted development tools to accelerate research, coding, testing, documentation, and troubleshooting. <br><br>Review and validate AI-generated work rather than accepting it without verification. <br><br>Learn unfamiliar systems and technologies as needed and share what you discover with the team. <br> <br>Knowledge, Skills & Abilities <br><br>Strong foundational SQL skills and experience working with relational data. <br><br>Working knowledge of Python, R, or another language used for data processing and automation. <br><br>Some experience building, modifying, or supporting ETL/ELT pipelines. <br><br>Familiarity with databases, data warehouses, APIs, scheduled jobs, or cloud-based data services. <br><br>Basic experience with Git and modern software-development practices. <br><br>An ability to investigate unfamiliar problems, test assumptions, and communicate findings clearly. <br><br>A dependable approach to execution, documentation, and follow-through. <br><br>Genuine curiosity and a willingness to learn technologies outside your current experience. <br><br>Practical experience using AI coding assistants or language models as part of a development workflow. <br><br>Good judgment about validating AI-generated code and protecting confidential or sensitive company information.
<p>For our client, we are seeking a Data Scientist to develop advanced analytics, predictive models, and machine learning solutions that support strategic business decisions. This individual will work with large datasets, identify meaningful patterns, and collaborate with technical and business teams to deliver actionable insights through statistical analysis, data modeling, and artificial intelligence.</p>
We are looking for a Software Engineer to join a contract opportunity with the potential to become permanent, based in New York, New York. This position will play a key role in shaping technical architecture across integrations, platform security, data flow, and release readiness within a Workday-focused environment. The ideal candidate brings strong engineering judgment, hands-on integration expertise, and the ability to guide technical standards while partnering with stakeholders across the organization.<br><br>Responsibilities:<br>• Direct the overall strategy for the integration ecosystem, including monitoring system health, maintaining technical inventories, and planning future enhancements across connectors, Studio solutions, and downstream consumers.<br>• Create and evaluate integration designs while establishing best practices for development, exception management, operational logging, and technical documentation.<br>• Partner with security stakeholders to define and maintain a robust tenant security framework covering access controls, business process security, and integration-related permissions.<br>• Assess the technical implications of platform updates and version changes, leading regression planning and validation efforts to reduce production risk.<br>• Investigate complex production issues affecting integrations, identify underlying causes, and implement durable corrective actions.<br>• Design and support advanced platform solutions such as Extend, Prism, or reporting capabilities when required by business needs.<br>• Promote modern engineering practices by introducing AI-supported development approaches, automated testing, and continuously updated technical knowledge assets.<br>• Provide technical leadership to engineers through coaching, design oversight, and participation in the interview process for new team members.