Forward Deployed Engineer

Become a Forward Deployed Engineer

Forward deployed engineers (FDEs) are software engineers who work directly with a customer to build, adapt, deploy, and operate software inside that customer's real production environment. Where a product engineer builds general capability for every user, an FDE works against one customer's data, APIs, and workflows, and increasingly delivers AI applications and agents. This role rewards people who can code and talk to customers at the same time, and this track builds both skills.

Build AI Applications That Work in the Real World

You'll go from calling LLM APIs to building complete AI systems:

• Use the OpenAI API and Responses API, and write effective prompts
• Create embeddings and build retrieval-augmented generation (RAG) applications
• Build LLM applications and tool-using agents with LangChain and LangGraph
• Connect LLMs to external systems with the Model Context Protocol (MCP)
• Measure and improve application quality with LangSmith
• Understand the LLMOps lifecycle and the principles of responsible AI

Strengthen Your Engineering Foundations

Production work depends on solid engineering habits. You'll learn version control with Git, including branches and remote repositories, and apply Python software engineering principles such as modularity, documentation, and automated testing.

Serve and Operate Your Applications

Learn to build robust APIs with FastAPI, handling requests, validation, and asynchronous execution. Then prepare AI-powered services for production with authentication, rate limiting, versioning, logging, and monitoring.

Communicate With Customers

Technical work only matters if the customer can act on it. You'll learn how to present data and translate technical results into actionable insights for non-technical stakeholders.

Launch Your Career as a Forward Deployed Engineer

By the end of this track, you'll be able to:

• Build and integrate LLM applications and agents with external data and tools
• Evaluate and monitor AI applications for quality and reliability
• Write well-structured, documented, and tested Python code
• Serve AI models and applications as secure, production-ready APIs
• Explain technical decisions and results to non-technical stakeholders

Start this track to build the engineering and customer skills that forward deployed AI roles ask for.