Lead .NET AI-Native Software Engineer

We are looking for a Lead .NET AI-Native Software Engineer to own the architecture of AI-based features for a measurement products platform and ship them against an established AI/data platform. This role spans natural-language query, summarization, intelligent validation and exception handling and workflow assistance, with integration into a model gateway, prompt registry, retrieval services and vector stores. The outputs feed regulated measurement workflows, so evaluation, auditability and human-in-the-loop patterns are core parts of the job, and the engineer will be accountable for the work of a small engineering team.

Responsibilities

• Own the architecture of AI features and ship them: natural-language query, summarization, intelligent validation and exception handling, workflow assistance
• Establish and evangelize reusable AI feature patterns for retrieval, evaluation and guardrails so teams do not reinvent them per product
• Implement RAG end-to-end: chunking, embeddings, hybrid search, reranking, grounded responses with citations
• Apply prompt and context engineering, including agentic flows where they add value
• Define evaluation discipline: golden datasets, offline eval suites, LLM-as-judge approaches and per-release regression checks
• Define and document complex requirements with stakeholders across product features, evaluation criteria and responsible-AI constraints
• Mentor engineers on LLM integration and evaluation, and be accountable for the work of a small engineering team
• Manage cost, latency and reliability through caching, fallbacks, token budgets and graceful degradation
• Apply responsible-AI practice: tenant data isolation, auditability and OWASP LLM Top 10 mitigations
• Implement telemetry via Application Insights and Serilog

Requirements

• 8+ years of software engineering experience in .NET (C#) and/or Python, with lead-level ownership of AI feature architecture across one or more products
• Deep experience shipping LLM-based features to production, including tool and function calling, structured outputs and streaming via Azure OpenAI / Azure AI Foundry, OpenAI or Anthropic APIs
• Working knowledge of modern AI/data platform components: model gateway, prompt registry, vector stores, embedding pipelines, evaluation frameworks, LLM observability and guardrails
• Judgment about where AI adds product value and where deterministic logic is the better tool
• Solid SQL fundamentals and API integration skills
• Strong documentation and standards habits: architecture docs in Azure DevOps Wiki, code review and testing discipline
• Hands-on experience using AI coding agents in the SDLC (GitHub Copilot, Claude, or equivalent)
• Experience working in agentic automation pipelines: AI-driven PR review and QA acceptance flows triggered by ADO work item tags
• English proficiency at B2 level or higher