Senior Microsoft Forward Deployed Engineer - Gps

Senior Microsoft Forward Deployed Engineer focused on building and deploying GenAI-enabled solutions and agentic platforms for enterprise clients. The role involves translating business needs into AI solutions, developing scalable AI engineering patterns, and applying architecture decisions for quality, safety, latency, and cost. Requires hands-on experience with Azure AI, RAG, and M365 Copilot extensibility.

What you'd actually do

  1. Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  2. Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  3. Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  4. Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  5. Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.

Skills

Required

  • software engineering
  • data engineering
  • data science
  • analytics engineering
  • GenAI/LLM-powered solutions
  • Microsoft Azure
  • Azure AI Foundry
  • Azure OpenAI
  • Azure AI Search
  • RAG
  • Copilot Studio
  • M365 Copilot extensibility
  • Python
  • TypeScript
  • C#
  • production-quality code
  • testing
  • CI/CD
  • logging
  • versioning
  • documentation
  • Semantic Kernel
  • AutoGen
  • tool/function calling

Nice to have

  • cloud environments (AWS, Azure, and/or Google Cloud)
  • common platform services (storage, compute, IAM, networking)
  • Spark
  • Airflow
  • dbt
  • streaming
  • data modeling
  • ML/data science
  • feature engineering
  • experimentation
  • model evaluation
  • MLOps/LLMOps practices
  • evaluation frameworks
  • model monitoring
  • prompt management
  • integrating LLM solutions with enterprise systems
  • APIs
  • microservices
  • event-driven architectures
  • Microsoft Fabric
  • Synapse

What the JD emphasized

  • building and deploying GenAI/LLM-powered solutions in client or production environments
  • Azure AI Foundry and Azure OpenAI hands-on experience
  • Azure AI Search with real RAG implementation experience
  • Copilot Studio and/or M365 Copilot extensibility
  • Semantic Kernel or AutoGen; agentic patterns; structured output and tool/function calling

Other signals

  • GenAI-enabled solutions
  • agentic platforms
  • human-in-the-loop controls
  • model risk
  • GenAI/LLM-powered solutions
  • RAG implementation
  • Copilot Studio
  • M365 Copilot extensibility
  • agentic patterns
  • tool/function calling