Job Title: Senior Full Stack .Net Engineer (Angular expertise)
Location: Chicago, IL (Hybrid 3 Days Work from Office)
Employment Type: Contract Role
Experience Required: 8+ Years
Educational Qualification: Engineering Degree BE / ME / B.Tech / M.Tech / B.Sc / M.Sc (Technical certifications in multiple technologies are desirable).
Role Overview:
We are seeking an experienced Senior Full Stack .Net Engineer (Angular expertise) to turn our Data Insight proof of concept into a production application. The product helps users explore healthcare reporting data, ask follow-up questions, and understand findings supported by source evidence. You will build agentic workflows and the user experience around them, with ownership of evaluation and quality pipelines that make the application reliable as it evolves.
Key Responsibilities:
Agentic Applications & Workflows: Build and operate agentic applications that interpret user intent, manage conversation context, call tools and APIs, and carry out multi-step analysis with appropriate user review.
Full-Stack Development: Develop the Angular user experience, .NET APIs, and Python agent services, integrating with existing reporting systems, authentication, and data access controls.
Evaluation Pipeline Ownership: Curate representative datasets with domain experts, define scoring rubrics and acceptance criteria, and combine automated checks with human review.
Quality & Accuracy Assurance: Evaluate answer correctness, supporting evidence, tool selection and execution, and end-to-end task success, including ambiguous requests, unsupported questions, and failure scenarios.
CI/CD & Release Gates: Integrate evaluations and regression tests into CI/CD. Version prompts, evaluation datasets, and configuration; compare changes against baselines and enforce quality gates before release.
Production Monitoring: Monitor production quality, latency, cost, and failures through traces and user feedback. Turn observed failures into reproducible test cases and measurable improvements.
Reliability & Security: Implement reliable execution with timeouts, retries, cancellation, durable state, and recovery, while protecting sensitive data and enforcing authorization at tool and data boundaries.
Collaboration & Traceability: Work with product owners and domain experts to validate analytical findings, preserve source traceability, and communicate uncertainty and application limitations clearly.
Mandatory Technical Skills & Qualifications:
Professional software development experience, including delivery and support of secure, scalable enterprise applications.
Hands-on experience building agentic applications using large language models, tool calling, structured outputs, prompt and context design, and multi-step workflows.
Practical experience building evaluation and quality pipelines for AI applications, including test datasets, scoring criteria, regression analysis, and human review (with the ability to explain how evaluation results informed a release or quality improvement).
Strong full-stack development skills with Angular, .NET Web APIs, and Python, including integration with existing enterprise services.
Strong SQL, relational data modeling, and data analysis skills, with attention to numerical accuracy, missing data, and traceability of results.
Experience with cloud-native application development on Azure, CI/CD, automated unit/integration testing, and end-to-end testing.
Experience with authentication, authorization, secure API design, observability, and reliable asynchronous processing.
Strong problem-solving and communication skills, with the ability to work independently and collaborate with product, engineering, and domain experts.
Preferred Qualifications:
Experience with retrieval-augmented generation (RAG), including document ingestion, retrieval, grounding, and retrieval quality evaluation.
Experience with healthcare analytics, enterprise reporting, or other applications that require careful handling of sensitive data and verifiable analytical results.
Experience taking AI prototypes into production and improving quality, latency, and operating cost using evaluation and production evidence.
Proven experience architecting and delivering systems using agentic IDEs, including defining architectural intent, breaking features into agent-executable tasks, governing AI autonomy (guardrails, permissions, reviews), and integrating agentic workflows into CI/CD pipelines.
Strong understanding of the security implications of autonomous code execution, compliance, auditability, traceability, and AI-assisted SDLC operating models.