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Forward-Deployed AI Engineer
Embed with a customer team and ship their AI feature in weeks, not quarters.
You sit inside the customer's codebase, learn their data, and ship a working AI integration end-to-end. Popularised by Palantir and now standard at Sierra, Decagon, Hex, and the major foundation-model labs. Pay is hybrid engineering + GTM; the role rewards people who can read a Slack channel, a SQL schema, and a roadmap in the same afternoon.
Skills profile
What hiring managers actually weigh.
Recommended paths
Take them in order. Each builds on the previous.
90-day roadmap
An honest, week-by-week plan. Adjust to your weekly time budget.
- 1
Ship-velocity base
~3 weeks- Build one end-to-end RAG feature against a real public dataset
- Wire structured outputs + a 30-case eval set you trust
- Land a clean deploy on Vercel or Fly with logs you can grep
- 2
Customer-shaped engineering
~4 weeks- Practise reading an unfamiliar codebase in under 90 minutes — clone 3 open-source repos, write a one-page architecture note for each
- Add an agent loop with tool-use against a customer-style schema (Postgres + Slack-like message corpus)
- Instrument latency, cost, and accuracy as one dashboard
- 3
Land the role
~3 weeks- Publish a write-up of a 1-week "FDE simulation" project on your blog or GitHub
- Pass the Applied GenAI Engineer pack on CertQuests
- Apply to 10 FDE postings — lead each application with a 5-line "here is what I would ship in week 1" plan
Certifications worth taking
Practice & certify on CertQuests after completing the course.
View the role-specific practice pack on certquests.comCareer outcomes
Realistic next steps after completing the roadmap.
- FDE / Solutions Engineer roles at Sierra, Decagon, Hex, Glean, Anthropic, OpenAI
- Founding engineer at AI-first startups — same skill stack, more equity
- Bridge into product or sales engineering once the eng credential is set