Senior AI Engineer with Microsoft Azure

We are looking for a Senior AI Engineer with Microsoft Azure expertise to take validated prototypes and make them survive production: evals, guardrails, security, cost and scale. You will build agentic systems on the Azure stack and code AI-first every day, with the commits to prove it. We value an 80% mindset and 20% skills approach - frameworks change quarterly, and we don't hire for one. What we can't teach is evaluation-driven engineering discipline and the honesty to say what a demo hides.

Responsibilities

• Industrialize prototypes into production services on Azure - Azure AI Foundry / Azure OpenAI - from build-ready pack to a system real users depend on in weeks
• Build agentic systems properly, choosing orchestration frameworks, RAG pipelines, vector DBs, knowledge graphs and MCP-based tool integration by need and engineer them for change
• Build the eval harness first: golden sets, regression evals and guardrail tests wired into CI, with quality measured on every change
• Engineer the guardrails, including input/output filtering, grounding and citation, PII protection, rate limits and human escalation paths
• Deliver full stack services in Python and/or Java Spring Boot along with TypeScript/Angular front ends
• Run production engineering end-to-end, covering CI/CD, observability with traces on every LLM call, cost and latency management and model-version churn absorbed by design
• Build security and compliance in, respecting data classification boundaries in prompts, stores and logs, externalizing secrets and making every AI decision auditable
• Iterate from real usage through hypercare, tuning and fixes based on evidence, and package patterns that worked for the next pod

Requirements

• 3+ years of experience shipping LLM/agentic systems in production with real users, with a defined eval approach and scale
• Proficiency in Python, Java Spring Boot and/or TypeScript/Angular
• Expertise in Azure PaaS and Azure AI services
• Skills in agentic frameworks, vector DBs, knowledge graphs and MCP
• Competency in prompt and context engineering
• Background in CI/CD and observability, having operated what you built
• Familiarity with daily AI-assisted engineering, coding with AI agents and demonstrating the workflow live
• English proficiency at B2 level or higher