AI Engineer vs Forward Deployed Engineer: Which Role Fits You?

Bashiri Smith · Facebook reel · 2026-09-09 · 1:08 · 8,127 views · Open on Facebook

Topics: Resume, Job Search & Interviews, Start Here: Roadmaps & Strategy, Retrieval-Augmented Generation (RAG) · Level: beginner

Summary

The video compares the AI engineer and forward-deployed engineer (FDE) roles side by side. Both need the same technical base: software engineering, embeddings, tool calling, retrieval, and evaluation. An AI engineer goes deep on building AI features into a product. An FDE works directly with customers to turn vague requests into systems that ship in the customer's real workflow. The creator uses a support-agent example to show how the day-to-day work and success metrics differ.

Key points

• AI engineer: builds AI features into a product, such as RAG pipelines, AI agents, and the APIs that power them.
• Forward-deployed engineer: works directly with customers to find where AI can help, then builds it into their actual workflow.
• Shared foundations: strong software engineering, plus embeddings, tool calling, retrieval, and model evaluation.
• FDEs also need customer-facing skills, like walking into a meeting and turning a vague request into a system they can ship.
• Support-agent example (AI engineer): build hybrid search, add a re-ranker, and test whether answers are accurate.
• Support-agent example (FDE): connect the agent to the customer's ticketing system, handle permissions, and work with the support team to get it into production.
• Metrics: both track answer quality, latency, cost, and reliability. FDEs also track whether the team actually uses the tool and resolves tickets faster.
• Choose AI engineer if you like building products and going deep into systems. Choose FDE if you like customers and messy business problems and are already a skilled AI engineer.

Resources mentioned

• BASWE.Ai Engineer (Skool community) · community · skool.com · paid
  The creator's paid community and program, with an AI learning roadmap (including the full ops and evaluation track), daily calls with engineers and recruiters, resume and portfolio help, and a job-search pipeline.
  Also in: Basic RAG Pipeline in 60 Seconds: From Documents to Grounded Answers (Bashiri Smith on Facebook · notes), Pointer to Bashiri Smith's Complete AI Engineer Roadmap for 2026 (Bashiri Smith on Facebook · notes), Step-by-Step Roadmap to a $200K+ AI Engineering Role (Bashiri Smith on Facebook · notes), How to Evaluate a RAG Pipeline: Retrieval vs. Generation (Interview Answer) (Bashiri Smith on Facebook · notes) and 76 more

Try this

• Decide which role fits you: deep product and system building (AI engineer) or customer-facing problem solving (forward-deployed engineer).
• Build strong software engineering foundations plus embeddings, tool calling, retrieval, and model evaluation.
• Get skilled as an AI engineer before moving into a forward-deployed role.
• Practice measuring answer quality, latency, cost, and reliability for AI systems.
• Customer-support AI agent using hybrid search plus a re-ranker, with tests for answer accuracy.
• Connect a support agent to a ticketing system with permission handling, and measure whether tickets get resolved faster.