<p>We are looking for a talented and motivated <strong>Software Engineer II</strong> to join our innovative IT team. As a Software Engineer II, you will be responsible for designing, developing, and maintaining software applications using modern technologies. You will work on both front-end and back-end development, ensuring seamless integration and optimal performance. Your role will involve collaborating with cross-functional teams to deliver high-quality software solutions that meet business requirements.</p><p><br></p><p>This role offers the opportunity to work on cutting-edge software solutions, improve system efficiency, and contribute to strategic IT initiatives. If you are passionate about software engineering and thrive in a dynamic environment, we’d love to hear from you!</p><p><br></p><p><strong>What You'll Do</strong></p><ul><li>Develop and maintain web applications using modern front-end frameworks such as React or Angular.</li><li>Design and implement RESTful APIs and microservices using C#.</li><li>Work with cloud platforms like Azure or AWS to deploy and manage applications.</li><li>Implement CI/CD pipelines using tools like Azure DevOps or GitHub Actions.</li><li>Collaborate with UX/UI designers to create intuitive and responsive user interfaces.</li><li>Write unit and integration tests to ensure code quality and reliability.</li><li>Participate in code reviews and provide constructive feedback to peers.</li><li>Troubleshoot and resolve software defects and production issues.</li><li>Design and contribute to an AI agent platform, enabling intelligent automation, workflow orchestration, and integration with enterprise systems.</li></ul><p><br></p>
<p>Robert Half, one of FORTUNE’s World’s Most Admired Companies and a Fortune 100 Best Companies to Work For is hiring for a Data Engineer III to join the ATI Data Science Innovation department.</p><p><br></p><p>Solution Design & Technical Leadership</p><ul><li>Lead architecture and design of complex data pipelines on Databricks lakehouse architecture (Unity Catalog, Delta Lake, Structured Streaming)</li><li>Define technical approach for data engineering initiatives, mentor less-senior engineers, and set standards for code quality through leadership and code reviews</li><li>Design and build data foundations that enable AI/ML capabilities — feature stores, embedding pipelines, vector search indexes, and model training datasets</li><li>Align data engineering solutions with business strategy, including support for Agentic AI workloads</li></ul><p>Data Infrastructure & Platform</p><ul><li>Own health, scalability, and modernization of data infrastructure with Databricks as the strategic platform — including workload migration, compute optimization, and Unity Catalog adoption</li><li>Optimize pipeline performance (Delta Lake table layouts, clustering, Z-ordering) and establish monitoring/alerting best practices with clear SLAs</li><li>Build data infrastructure supporting Agentic AI systems — real-time data access layers, context retrieval pipelines, and agent-accessible data services</li><li>Collaborate cross-functionally with DevOps, Platform Engineering, and MLOps roles to integrate data solutions into the broader technology environment and shared AI infratstructure – Mlflow registries, feature stores, and agent orchestration layers</li><li>Provide consultation to Senior Leadership on complex projects and drive continuous improvement initiatives</li></ul><p>Data Quality, Governance & Collaboration</p><ul><li>Champion data governance at all layers for data, models, and AI assets</li><li>Implement data quality strategies (master data management, validation rules, Delta Live Tables expectations) to ensure trust in enterprise data</li><li>Serve as liaison across data engineering, AI engineering, and business teams; promote data literacy and stewardship</li></ul><p><br></p>
<p>Robert Half is seeking a Software Engineer II – AI Engineer who will analyze, design, program, debug, test, implement, deploy, and support software enhancements and new applications using Generative AI technologies. This role contributes to the development and production deployment of GenAI-enabled applications, including LLM-powered workflows, RAG pipelines, and AI-driven user experiences. </p><p> </p><p>This role supports SDLC documentation across all phases, with a focus on deployment, evaluation, observability, safety, and monitoring. It also interacts with users to define requirements and support applications in production. </p><p><strong>What You’ll Do</strong> </p><ul><li>Develop and modify application modules, including GenAI components. </li><li>Build prompt workflows, retrieval layers, APIs, and cloud services. </li><li>Troubleshoot production issues, including latency, hallucinations, and errors. </li><li>Provide Level II production support for deployed systems. </li><li>Design components, including LLM integrations and RAG pipelines. </li><li>Implement CI/CD pipelines, containerization, and release processes. </li><li>Develop RAG pipelines with embeddings, chunking, and vector search. </li><li>Apply prompt engineering techniques, including few-shot prompting and structured outputs. </li><li>Evaluate models for accuracy, relevance, and hallucination risk. </li><li>Implement safety guardrails, including PII protection and prompt-injection defense. </li><li>Execute testing, including unit, integration, and GenAI evaluation testing. </li><li>Monitor production systems for latency, cost, usage, and errors. </li><li>Support incident management with fallback and recovery strategies. </li></ul><p><br></p>
<p>We are looking for a Data Labeler to support high-quality dataset preparation for machine learning initiatives in San Francisco, California. This Long-term Contract position focuses on reviewing and organizing text, image, audio, and video content so AI models can be trained with reliable, well-structured information. The ideal candidate brings strong editorial judgment, accuracy, and the ability to apply detailed standards consistently across large volumes of content.</p><p><br></p><p>Responsibilities:</p><p>• Evaluate and label content across multiple data formats, including written material, images, audio files, and video, using defined annotation standards.</p><p>• Apply tags, classifications, and descriptive markers to datasets so they can be used effectively in AI and machine learning training workflows.</p><p>• Inspect content for quality, completeness, and consistency, correcting issues and flagging unclear or unusual cases for further review.</p><p>• Annotate visual assets by identifying relevant elements, outlining objects, or marking important features based on project requirements.</p><p>• Review language-based content to classify topics, sentiment, entities, intent, or other attributes needed for model development.</p><p>• Transcribe and enrich audio-based materials when required, ensuring accurate interpretation and documentation.</p><p>• Maintain productivity and quality benchmarks while handling recurring tasks with a high level of precision and organization.</p><p>• Partner with technical and quality teams to refine labeling practices and improve the usefulness of training datasets.</p>