Senior AI Engineer with Microsoft Azure

EPAM Systems Inc

  • Atlanta, GA
  • 28 days ago

    Highlights

    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. 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.

    Numbers & Facts

    LocationAtlanta, GA

    Description

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    Senior AI Engineer with Microsoft Azure

    Remote in Georgia, & 4 others

    AI Solution Engineering

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    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 dont hire for one. What we cant 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

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