Senior Forward Deployed Engineer, Microsoft AI & Data

Deloitte Deloitte · Consulting

Senior Forward Deployed Engineer at Deloitte focused on building and deploying GenAI solutions for enterprise clients, working with Microsoft AI & Data platforms. The role involves client engagement, solution engineering, and delivering production-quality AI-enabled applications and agentic platforms.

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

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • 1+ years of experience building reliable, maintainable, and well-documented code
  • Ability to travel 50%, on average

Nice to have

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management
  • Experience integrating LLM solutions with enterprise systems via APIs, microse

What the JD emphasized

  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with Microsoft AI&Data including hands on experience with Azure AI Foundry.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions

Other signals

  • GenAI-enabled solutions
  • enterprise-scale impact
  • production-quality code
  • client-facing