Senior Technical Support Engineer

Microsoft Microsoft · Big Tech · Charlotte, NC +4 · Technical Support Engineering

This role focuses on owning and troubleshooting complex AI initiatives, including model selection, RAG, agentic pipelines, prompt design, and safety guardrails. The engineer will drive the roadmap, manage the AI development lifecycle (Responsible AI, model risk, privacy, compliance), and validate outcomes. They will also own customer supportability and evangelize AI solutions. Requires experience delivering AI/ML products to production and hands-on knowledge of the AI/ML product lifecycle, including evaluation and optimization of RAG, agent-based, or LLM-powered solutions.

What you'd actually do

  1. You'll own complex AI initiatives end to end: partnering with applied science and engineering to shape architecture and integrated customer solutions — model selection, retrieval-augmented and agentic pipelines, prompt and tooling design, and safety guardrails.
  2. You'll drive the roadmap, schedules, and staging and release plans against clear objectives; lead governance across the AI development lifecycle (Responsible AI review, model-risk, privacy, and compliance); and validate outcomes against real telemetry.
  3. You'll own the customer supportability experience and act as a trusted technical person who evangelizes and drives the right work.

Skills

Required

  • Bachelor's Degree in Computer Science, Information Technology (IT), or related field AND 5+ years technical support, technical consulting experience, or information technology experience OR equivalent experience.
  • 8+ years of experience in Technical Program Management, Product Management, or a related field, including 2+ years delivering AI/ML, Generative AI, or data-intensive products to production.

Nice to have

  • Microsoft Technology Certifications
  • Industry IT-Based Certifications (e.g. Comp-TIA, CCNA, ISC2)
  • Demonstrated success leading complex cross-functional programs, managing multiple stakeholders, and driving execution through influence without direct authority.
  • Hands-on knowledge of the AI/ML product lifecycle, including data preparation, model training/fine-tuning, prompt engineering, evaluation, deployment, and production monitoring.
  • Proven ability to evaluate and optimize model performance, balancing quality, latency, scalability, and cost across RAG, agent-based, or LLM-powered solutions.
  • Experience defining and implementing Responsible AI, model governance, risk management, and compliance practices throughout the product lifecycle.
  • Strong written and verbal communication skills, with a track record of translating complex technical concepts into actionable business outcomes for technical and non-technical audiences.

What the JD emphasized

  • delivering AI/ML, Generative AI, or data-intensive products to production
  • Hands-on knowledge of the AI/ML product lifecycle
  • evaluate and optimize model performance
  • RAG, agent-based, or LLM-powered solutions
  • Responsible AI review, model-risk, privacy, and compliance

Other signals

  • AI transformation for our customers
  • AI technology to help consumers, businesses, partners, and more
  • own complex AI initiatives end to end
  • delivering AI/ML, Generative AI, or data-intensive products to production
  • Hands-on knowledge of the AI/ML product lifecycle
  • evaluate and optimize model performance
  • RAG, agent-based, or LLM-powered solutions