Forward Deployed Engineer for AI Systems

A Forward Deployed Engineer for AI Systems combines AI engineering, customer collaboration, and production implementation. As organizations move AI systems from prototypes into production, they need engineers who can translate customer needs into clear technical requirements, build production-ready systems, communicate effectively with stakeholders, and support systems from proof of concept through production rollout and ongoing use. This course develops the technical, delivery, and communication skills required for the role. I developed this course based on my research in intelligent computing, adaptive AI, and neural networks, along with years of studying how AI systems move from design to production. One recurring challenge stood out: capable engineers could build technically strong models but struggled to translate them into production systems that addressed customer needs. This course provides a practical framework for developing the technical, delivery, and consulting skills required of an FDE for AI Systems. You'll follow the complete life cycle of an FDE engagement, from customer discovery and project scoping through proof-of-concept delivery and production handoff. You’ll examine core AI system design and delivery topics, including RAG pipelines, agent and multi-agent architectures, harness engineering, framework selection, and production evaluation. You’ll apply these concepts through realistic case studies. This course is designed for professionals with backgrounds in software engineering, machine learning, or AI infrastructure. It develops the practical judgment required to design and deliver production AI systems and prepares you to discuss system design, delivery trade-offs, and customer-facing decisions in FDE interviews. It provides a structured foundation for both the role and the interview process.