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We’re entering a new era, one defined by the power of AI to reshape what’s possible. At Microsoft, we’re not just exploring the future of AI, we’re building it. Our mission is ambitious: to create an open, next-generation AI platform that empowers organizations to unlock unprecedented value. Imagine a world where businesses can summon intelligent, bespoke AI agents that accelerate decision-making, enhance productivity, and transform customer experiences. This is your chance to help shape that future. As a Forward Deployed Engineer (FDE), you’ll operate at the intersection of advanced AI technology and real-world business impact — embedded directly with customers to bring bold ideas to life.
Job Responsibility:
Be a hands-on builder working in close partnership with customers to address their most pressing challenges
Immerse yourself in their mission to design and deliver AI-powered solutions that create measurable impact
Move quickly from concept to prototype to production, iterating alongside stakeholders
Work will span engineering data pipelines and integrations, building custom applications, and deploying scalable workflows
Remain accountable for monitoring, refining, and driving adoption of what you build
As a bridge between the customer environment and Microsoft’s engineering teams, share insights from the field that influence the direction of our AI platforms
Contribute to knowledge sharing, mentor peers, and help set the standards for how Microsoft delivers AI-first transformation
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check upon hire/transfer and every two years thereafter
Nice to have:
Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience
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
Capable of optimizing, prompting and finetuning AI-based solutions for performance, accuracy, and scalability
Experience coaching and growing engineers within the team