Forward Deployed Engineer

Microsoft Microsoft · Big Tech · Bengaluru, KA, IN · Software Engineering

This role involves partnering directly with customers to translate real-world problems into production-grade AI solutions using cutting-edge AI innovation. The Forward Deployed Engineer will design, develop, and deploy sophisticated AI-powered systems at scale, engineer data pipelines, build custom applications, and deploy scalable workflows. The role also involves monitoring, refining, and driving adoption of built solutions, and sharing field insights to influence AI platform direction. Requires a strong balance of AI understanding and practical software engineering experience, with a focus on generative AI and ML/LLM-based solutions in production.

What you'd actually do

  1. As a Microsoft Forward Deployed Engineer, you’ll be a hands-on builder working in close partnership with customers to address their most pressing challenges.
  2. Your work will span engineering data pipelines and integrations, building custom applications, and deploying scalable workflows that bring AI to life in critical business processes.
  3. Importantly, your role doesn’t end at launch -- you’ll remain accountable for monitoring, refining, and driving adoption of what you build.
  4. As a bridge between the customer environment and Microsoft’s engineering teams, you’ll also share insights from the field that influence the direction of our AI platforms.
  5. Finally, as part of a growing FDE community, you’ll contribute to knowledge sharing, mentor peers, and help set the standards for how Microsoft delivers AI-first transformation.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 1+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • Competence with DevOps practices, including CI/CD pipelines, containerization, and infrastructure-as-code.
  • Solid understanding and successful demonstration of system security, scalability, reliability, and maintainability.
  • Practical Experience with AI/LLMs: Experience designing and implementing ML/LLM-based solutions in production environments.
  • Experience leveraging generative AI technologies to develop innovative and user-focused product features.

What the JD emphasized

  • production-grade AI solutions
  • production environments
  • deploy scalable workflows

Other signals

  • customer-facing AI solutions
  • deploying scalable workflows
  • generative AI technologies