<p><strong>Cloud Engineer II</strong></p><p><strong>This Statement of Work covers a six-week Phase 0 proof-of-concept engagement. Phase 0 is intended to validate feasibility, not to deliver an enterprise-scale production service.</strong></p><p><strong>This position will deploy an open-weight model endpoint in the client's infrastructure in AWS, connect it to OpenCode, and provide enough evidence for the client to decide whether to proceed to Phase 1.</strong></p><p><strong>The Phase 0 business case is based on validating whether open-weight inference can work for non-Opus coding workloads, with success criteria including model quality, latency, throughput, end-to-end developer flow, developer satisfaction, and a go/no-go decision for the next phase.</strong></p><p><br></p><p><br></p><p>Responsibilities</p><p>• Deploy and configure an AWS-hosted, open-weight coding model endpoint using client-provided infrastructure.</p><p>• Configure model-serving runtime, GPU allocation, endpoint exposure, health checks, service routing, basic error logging, credential handling, and repeatable deployment artifacts.</p><p>• Expose the model endpoint through an OpenAI-compatible API path capable of supporting representative coding prompts.</p><p>• Configure and validate OpenCode integration with the model endpoint, including any required adapter, proxy, gateway, or compatibility layer.</p><p>• Demonstrate end-to-end OpenCode-to-model request flow for representative coding-agent workflows.</p><p>• Demonstrate representative coding-assistance use cases, including code completion, code explanation, unit test generation, refactoring assistance, error diagnosis, small feature implementation, tool usage, repository/file-context prompts where supported prompts and agent skills, and OpenCode/Open Spec workflows.</p><p>• Collect and save basic performance data in Grafana, including time to first token, end-to-end latency, tokens per second, concurrency behavior, error rate, GPU utilization, and memory utilization.</p><p>• Implement baseline observability for the POC, including logs, health checks, basic metrics, and simple dashboard or metric views where feasible.</p><p>• Provide reusable deployment and configuration artifacts, such as Helm values, Kubernetes manifests, scripts, runtime configuration, gateway/proxy configuration, runbook, troubleshooting notes, and environment assumptions.</p><p>• Support limited developer validation with a small client-designated pilot group if access, timing, and dependencies allow.</p><p>• Support a lightweight quality comparison between the open-weight model and client's current coding-assistant experience if time and access allow.</p><p>• Provide preliminary Phase 1 sizing inputs, including throughput observations, bottlenecks, latency drivers, scaling considerations, recommended AWS instance families, and remaining unknowns.</p><p>• Deliver a written final report covering architecture, deployment, OpenCode integration results, functional test results, performance measurements, technical gaps, security and operational considerations, cost and scale observations, reusable artifacts, and Phase 1 readiness.</p><p>• Deliver a clear Phase 1 go/no-go recommendation, including required changes, unresolved risks, and recommended next steps for AWS-based enterprise-scale implementation.</p><p>• Conduct a knowledge-transfer session with stakeholders at the end of the engagement.</p>
<p>We are looking for an experienced Sr. Cloud Engineer to lead the design and operation of secure, scalable cloud environments. This role focuses on building resilient multi-cloud infrastructure across AWS and Microsoft Azure while advancing automation, governance, and operational reliability. The ideal candidate brings strong expertise in Terraform, cloud architecture, and enterprise-wide security practices, along with a practical approach to performance monitoring and cost control.</p><p><br></p><p>Responsibilities:</p><p>• Build and manage multi-cloud infrastructure across AWS and Azure with a focus on security, scalability, and reliability.</p><p>• Create and enhance infrastructure automation using Terraform to standardize provisioning, configuration, and ongoing platform management.</p><p>• Establish enterprise cloud governance by designing landing zones, multi-account structures, and policy controls across AWS and Azure environments.</p><p>• Monitor platform health, security posture, compliance status, and service availability using native and third-party observability tools.</p><p>• Partner with application and infrastructure teams to develop backup, disaster recovery, high-availability, and failover solutions that support business continuity.</p><p>• Review cloud environments regularly to improve resource utilization, strengthen security controls, and reduce unnecessary spend.</p><p>• Advise stakeholders on cloud architecture, operational best practices, troubleshooting, and approaches for moving on-premises systems into cloud platforms.</p><p>• Design and maintain identity and access management models, including role-based access and federated identity solutions across cloud accounts and subscriptions.</p><p>• Produce and maintain clear technical documentation covering architecture standards, configurations, procedures, and support processes.</p><p>• Contribute to capacity planning, performance tuning, and long-term platform optimization initiatives across enterprise cloud services.</p>
We are looking for a Snowflake Data Engineer to build modern data solutions that support analytics, AI, and enterprise decision-making. This role will focus on creating reliable pipelines, scalable data models, and secure data products within a Snowflake environment. The position is based in Radnor, Pennsylvania, and offers the opportunity to work closely with engineering, security, product, and business teams on high-impact initiatives.<br><br>Responsibilities:<br>• Architect and maintain scalable data pipelines, transformation workflows, and structured data models within Snowflake to support reporting, analytics, and AI use cases.<br>• Develop and deploy AI and machine learning capabilities using Snowflake-native tools, including intelligent agents, search-driven experiences, and customer-facing applications where applicable.<br>• Define and manage semantic views and business logic layers that provide governed, consistent definitions for analytics and AI consumption.<br>• Implement and support data ingestion frameworks using technologies such as Kafka, Snowpipe, APIs, Openflow, and third-party connectors, including integrations with enterprise platforms like NetSuite.<br>• Create reusable engineering utilities and automation with SQL, SnowSQL or related Snowflake tooling, Python, and JavaScript when appropriate.<br>• Establish strong production standards through automated testing, data quality validation, observability, exception handling, and controlled deployment processes.<br>• Tune queries, pipelines, AI workloads, and data structures to improve performance, scalability, maintainability, and downstream usability.<br>• Design secure data-sharing solutions and data-product delivery patterns for internal stakeholders, external partners, and customers.<br>• Collaborate with platform administrators and security teams to align access controls, governance requirements, identity integration, and production readiness for Snowflake solutions.<br>• Investigate and resolve issues affecting pipelines, semantic models, applications, and data quality while partnering across technical and business teams to deliver durable solutions.
We are looking for an Azure Cloud Engineer – AI & Automation to join a contract opportunity based in Pennsylvania. In this role, you will help shape and support secure Azure environments while enabling AI-driven capabilities across cloud infrastructure, automation, and platform operations. This position is ideal for someone who enjoys balancing hands-on engineering with governance, reliability, and scalable delivery practices in a highly regulated environment.<br><br>Responsibilities:<br>• Create and support Azure-based solutions spanning infrastructure, connectivity, identity, storage, and managed platform services in line with enterprise architecture and security expectations.<br>• Develop and optimize deployment automation using infrastructure-as-code and modern release pipelines through tools such as Azure DevOps, GitHub Actions, Bicep, and Terraform.<br>• Operate and administer AI services across Azure AI Foundry, Azure OpenAI, Claude, and related platforms, including model setup, permission management, policy enforcement, evaluation, and live environment support.<br>• Establish and govern secure integrations for Model Context Protocol and connected enterprise systems by applying strong authentication, access controls, and data protection standards.<br>• Manage APIs, event-driven components, and security gateway configurations that enable AI services and automated workflows to connect with business applications reliably.<br>• Build retrieval-augmented AI solutions using Azure AI Search, embeddings, and vector-based data patterns to improve access to enterprise knowledge.<br>• Maintain and enhance automation solutions built with Power Automate, Logic Apps, and Copilot Studio, supporting integrations with Microsoft 365, Teams, SharePoint, and ServiceNow.<br>• Strengthen cloud governance through Azure Policy, tagging strategy, cost oversight, monitoring, logging, and operational observability tools such as Azure Monitor and Application Insights.<br>• Support Microsoft Fabric administration by overseeing tenant settings, workspace permissions, capacity controls, data access, and usage visibility across supported workloads.<br>• Contribute technical documentation, reusable standards, KPI/KRI reporting, change review activities, and incident or release support for cloud and AI environments.
We are looking for a Data Scientist to join a healthcare-focused technology team in Bala Cynwyd, Pennsylvania on a Long-term Contract basis. This position will support predictive analytics initiatives tied to state programs, quality oversight, compliance monitoring, and risk evaluation. The role is well suited for someone who can work comfortably across technical analysis, stakeholder communication, and team guidance while using modern Microsoft-based data tools.<br><br>Responsibilities:<br>• Build and refine predictive models that support healthcare analytics, quality measurement, compliance assessment, and risk-related reporting.<br>• Analyze complex datasets to uncover trends, generate actionable insights, and improve decision-making for program and operational stakeholders.<br>• Create interactive dashboards and reporting solutions in Power BI to present findings in a clear and business-friendly format.<br>• Use R, Python, SQL, and related tools to prepare data, perform statistical analysis, and develop repeatable analytical workflows.<br>• Work within Azure and Microsoft-based data environments, including SQL Server and MySQL, to manage and access structured data sources.<br>• Partner with analysts and business teams to translate technical results into practical recommendations for non-technical audiences.<br>• Provide day-to-day guidance and informal leadership within a small analytics team, helping coordinate priorities and support best practices.<br>• Contribute to data engineering and integration activities, including ETL processes and the use of tools such as Spark, Hadoop, and Kafka where needed.<br>• Leverage approved AI tools such as Copilot to improve efficiency in analysis, documentation, and reporting tasks.
We are looking for a Data Analyst to join a team in Somerset, New Jersey and turn complex information into actionable insight that strengthens fraud detection efforts. This contract opportunity with potential for a permanent role is ideal for someone who combines strong analytical thinking with practical experience identifying suspicious patterns, supporting investigations, and improving anti-fraud decision-making. The role offers the chance to work closely with business partners to interpret data, surface risk trends, and contribute to a more proactive fraud strategy.<br><br>Responsibilities:<br>• Examine large data sets to identify unusual activity, emerging fraud patterns, and indicators of potential risk.<br>• Create reports, dashboards, and analytical summaries that help stakeholders monitor fraud performance and make informed decisions.<br>• Partner with investigation and business teams to translate data findings into practical actions that support fraud prevention efforts.<br>• Evaluate transactional and behavioral information to uncover trends, root causes, and opportunities to reduce exposure.<br>• Support fraud investigations by gathering, organizing, and interpreting relevant data from multiple sources.<br>• Refine analytical methods and detection approaches to improve accuracy, efficiency, and responsiveness in anti-fraud initiatives.
We are looking for a Desktop Support Analyst to provide hands-on technical support for end users and departmental technology needs in Philadelphia, Pennsylvania. This Contract position focuses on maintaining reliable desktop systems, resolving hardware and software issues, and supporting a broad range of computing equipment used in day-to-day operations. The ideal candidate brings a service-focused approach, strong troubleshooting ability, and the confidence to work independently while collaborating with technical and non-technical stakeholders.<br><br>Responsibilities:<br>• Deliver desktop support by installing, configuring, repairing, and maintaining computers, operating systems, peripheral devices, and specialized research-related equipment.<br>• Investigate and resolve technical incidents, respond to user inquiries, and restore service quickly while escalating uncommon or higher-risk issues when needed.<br>• Guide employees on proper system and equipment use, helping them work effectively and follow established technology practices.<br>• Recommend appropriate hardware and software purchases by providing technical input, product guidance, and specification details for departmental needs.<br>• Review the local computing environment to identify opportunities for improved performance, reliability, and process efficiency.<br>• Participate in the assessment and rollout of technology solutions, including product testing, implementation support, and validation with end users.<br>• Maintain accurate records by updating service tickets, documenting assigned work, and keeping inventory information current.<br>• Support configuration and user administration tasks within Windows environments and Active Directory as part of daily desktop operations.
We are looking for a Web Analytics Specialist to support digital measurement and insight generation for a healthcare-focused organization in Philadelphia, Pennsylvania. This Long-term Contract role is ideal for a mid-level analyst who combines strong technical capabilities with sharp business judgment, turning complex web data into clear recommendations for cross-functional partners. The person in this position will help shape how marketing, campaign, and paid media performance are measured while contributing to a collaborative, insight-driven team environment.<br><br>Responsibilities:<br>• Design, update, and optimize Power BI dashboards that give stakeholders clear visibility into website, campaign, and funnel performance.<br>• Analyze digital behavior and marketing results to uncover trends, explain performance shifts, and translate findings into practical recommendations.<br>• Develop meaningful measurement frameworks and introduce new KPIs that improve how online engagement and conversion activity are evaluated.<br>• Use website analytics data to answer detailed business questions, including page-level interaction patterns and audience engagement across digital properties.<br>• Work closely with marketing, web, data, and engineering partners to align reporting needs, improve data usability, and support informed decision-making.<br>• Oversee recurring performance reporting while also responding to ad hoc analytical requests tied to evolving business priorities.<br>• Manage multiple stakeholder needs at once, ensuring deadlines are met without losing focus on quality or strategic value.<br>• Query and interpret data within Databricks and collaborate with engineering teams on data accessibility, structure, and analytics readiness.<br>• Support analytics tagging and tracking initiatives through tools such as Tealium and contribute to reporting environments connected to layered data models, including Silver and Gold data assets.
<p><strong>Data Scientist III </strong>(Supply Chain Optimization & Forecasting)</p><p>Long Term Contract</p><p>Hybrid Philadelphia, PA</p><p>Pay: Available on W2</p><p><strong>Overview</strong></p><p>We are seeking an experienced <strong>Data Scientist III</strong> to support a Supply Chain Planning Center of Excellence focused on forecasting, inventory optimization, and advanced analytics. This individual will design and deploy data science and operations research solutions that improve demand planning, inventory performance, and supply chain decision-making across complex business networks.</p><p>This role requires a combination of Data Science and Operations Research expertise. Candidates should be comfortable building machine learning models as well as optimization and linear programming solutions that support supply chain planning and inventory decisions.</p><p><strong>Key Responsibilities</strong></p><p>Forecasting & Data Science</p><ul><li>Develop and deploy time-series forecasting and machine learning models to improve demand planning performance.</li><li>Build and enhance demand forecasting models and machine learning solutions.</li><li>Develop inventory optimization, linear programming, and Operations Research models that improve planning decisions.</li><li>Analyze inventory performance, demand variability, and forecasting accuracy to improve business outcomes.</li><li>Translate business requirements into scalable analytical solutions.</li><li>Perform feature engineering, model development, validation, and statistical analysis using large-scale supply chain datasets.</li></ul><p>Inventory Optimization & MEIO</p><ul><li>Lead the development, enhancement, and ownership of Multi-Echelon Inventory Optimization (MEIO) models.</li><li>Translate business requirements, operational constraints, and planning policies into mathematical optimization models and decision-support tools.</li><li>Develop optimization logic that balances inventory investment, service levels, safety stock, lead-time variability, network constraints, and cost objectives.</li></ul><p>Optimization Engineering</p><ul><li>Build and maintain mathematical optimization models using commercial optimization solvers such as Gurobi or similar platforms.</li><li>Apply optimization techniques including linear programming, mixed-integer programming, scenario modeling, simulation, and uncertainty-aware optimization.</li></ul><p>Data Engineering & Operationalization</p><ul><li>Develop and maintain SQL-based ETL processes and data pipelines that support optimization and forecasting solutions.</li><li>Partner with data engineering teams to ensure data quality, availability, and reliability.</li><li>Create monitoring, governance, and documentation processes to support production-ready solutions.</li></ul>
We are looking for a Data Engineer to help build reliable data solutions that support reporting, analytics, and day-to-day business decisions in Princeton, New Jersey. This position focuses on creating scalable data flows, improving platform performance, and organizing data for efficient access across teams. The ideal candidate brings strong technical depth in pipeline development, database technologies, and cloud-based data environments.<br><br>Responsibilities:<br>• Build, enhance, and support scalable ETL workflows that move and transform data from multiple sources into trusted analytical platforms.<br>• Create and refine data models, storage structures, and warehouse solutions to improve accessibility, efficiency, and long-term maintainability.<br>• Monitor data processes to identify issues, strengthen reliability, and maintain high standards for accuracy, consistency, and performance.<br>• Partner with analytics, engineering, and business stakeholders to understand data needs and deliver practical data solutions.<br>• Optimize SQL Server and related data systems to support efficient querying, integration, and operational stability.<br>• Implement and maintain orchestration processes using tools such as Airflow or comparable workflow technologies.<br>• Contribute to cloud-based data infrastructure initiatives across platforms such as Azure and other enterprise cloud environments.
We are looking for a Data Engineer to join a growing team in Conshohocken, Pennsylvania within the financial services industry. In this role, you will build and enhance modern data pipelines and warehouse structures that support reporting, analytics, and business decision-making. You will partner with technical and business teams to deliver reliable, well-governed data solutions using Python, Azure Synapse Analytics, and related cloud technologies.<br><br>Responsibilities:<br>• Build and support scalable data pipelines using Python, including PySpark, within Azure Synapse Analytics notebooks and pipeline workflows.<br>• Design, load, and maintain warehouse structures in a massively parallel processing environment, applying dimensional modeling concepts such as facts and dimensions.<br>• Ingest and transform data from a range of sources, including APIs, databases, and flat files, to create dependable datasets for downstream use.<br>• Improve the efficiency and reliability of Azure Synapse processes by tuning queries, refining workloads, and addressing performance constraints.<br>• Partner with data architects, analysts, and other stakeholders to translate business needs into practical data models and engineering solutions.<br>• Establish validation routines and data quality controls to promote completeness, consistency, and accuracy across datasets.<br>• Monitor scheduled jobs and pipeline activity, troubleshoot failures, and implement corrective actions to maintain service levels.<br>• Document data flows, transformation logic, technical configurations, and operating procedures to support maintainability and knowledge sharing.<br>• Apply security, privacy, and governance standards to data solutions while supporting broader data platform initiatives such as lakes, lakehouses, and cataloging practices.
We are looking for a Data Engineer to join a Contract engagement supporting people analytics and HR-focused data initiatives in Philadelphia, Pennsylvania. This role is centered on designing, building, and refining scalable data pipelines and curated data assets using Azure Databricks and Azure Data Factory. The ideal candidate will be comfortable working hands-on with complex source data, translating business needs into reliable transformations, and delivering production-ready solutions with minimal oversight.<br><br>Responsibilities:<br>• Design, build, and maintain robust ETL and ELT workflows that support HR and workforce data products.<br>• Develop scalable data transformations using Python, SQL, Spark, and Azure Databricks to prepare high-quality datasets for downstream use.<br>• Orchestrate and monitor pipeline execution through Azure Data Factory to ensure dependable and timely data delivery.<br>• Analyze existing source systems and data structures to map requirements and create efficient ingestion and transformation logic.<br>• Partner with stakeholders across HR and analytics teams to turn business questions into practical engineering solutions.<br>• Improve data quality, performance, and reliability by applying modern engineering standards, testing practices, and documentation.<br>• Support integrations across HRIS and related platforms, including contributing to interface development where needed.<br>• Create production-ready datasets that enable reporting, workforce analysis, and broader people data initiatives.
We are looking for an experienced Data Engineer to support the design and delivery of scalable data solutions within the People and HR data domain in Philadelphia, Pennsylvania. This Long-term Contract position is ideal for someone who can step into an existing environment, learn source systems quickly, and build reliable data pipelines that support reporting and business analysis. The role centers on hands-on development using Azure Databricks, Spark, and Azure Data Factory, with an emphasis on creating production-ready data assets. Experience working with HR data and workforce-related systems will be highly valuable in helping translate business needs into dependable engineering solutions.<br><br>Responsibilities:<br>• Design, build, and maintain data pipelines that ingest, transform, and prepare HR and workforce data for downstream analytics and reporting.<br>• Develop scalable data processing solutions using Azure Databricks, Python, Spark, and SQL to support production-grade data products.<br>• Orchestrate and monitor data workflows through Azure Data Factory to ensure timely, accurate, and resilient data movement.<br>• Analyze existing data sources and business requirements to create efficient transformation logic and structured datasets.<br>• Collaborate with stakeholders across technical and functional teams to align data engineering deliverables with HR reporting and operational needs.<br>• Improve data quality, performance, and reliability by applying sound ETL practices, validation checks, and optimization techniques.<br>• Support integration efforts involving HR systems and related interfaces, including work connected to evolving source platforms when needed.<br>• Contribute to documentation, technical standards, and knowledge sharing to support maintainability and long-term solution success.