The Forward Deployed Engineer interview
FDE interview loops look like software engineering loops on paper, with a coding round, a system or case round and behavioural questions. What changes is the weight: most loops add a round where you break an open customer problem into steps, and many add a take-home you must defend decision by decision.
The pieces below are grouped in the order a candidate meets them. Each group starts with the piece to read first.
How the loop works
- FDE interviews: the coding round survives, but it is no longer the main filter
Cognition has reportedly dropped coding and system design altogether. Where coding rounds remain, the round that counts most is 45 to 60 minutes with a "customer" who holds back information on purpose.
- Algorithm practice prepares you for only one round of the FDE interview loop
In the round that decides the outcome, the interviewer gives you no clean input and output. You get a vague business goal, and they listen while you think out loud.
- FDE interview prep: enough DSA to pass, then focus on decomposition
Databricks asks you to write a dictionary-processing function in a notebook. OpenAI sets an implementation task split into several parts. Palantir gives you 60 minutes of decomposition on a problem that leaves out information on purpose, and it does not care whether you know Dijkstra by heart.
Take-home and project stories
- The FDE take-home: build an app that runs, then defend every decision in the walkthrough
A candidate who took OpenAI's take-home found that most of the grading seemed to turn on whether you could explain why each choice served the customer's need, not on the code alone.
- Telling project stories in FDE interviews: how to answer "What trade-offs did you make?"
The trade-off question checks whether you can see what you gave up, why you gave it up, and how you explained that to the customer.
Company loops
- Companies hiring FDEs now
Every company with open FDE roles, its role count and posted pay.
- Palantir FDSE interviews: how to practise the re-engineering and learning rounds
Neither round scores how quickly you find the bug. Both score how you track it down, and how you learn something new while someone watches.
What recruiters screen for
- What FDE recruiters look for: code gets you in, customer communication sets the ranking
You cannot work as an FDE without coding. Once candidates have shown they can code, what decides who gets hired is how well they communicate with customers and win them over.
- The FDE CV: drop the framework list, state deployment results with a baseline
People hiring forward deployed engineers read a CV looking for a result they can verify, so a line reading “LangChain, Kafka, Kubernetes” tells them almost nothing.
- Building an FDE portfolio repo: a simple agent, evals built from real failures, a README and a 3-minute video
A polished demo only proves the agent got it right once. A repo worth sending shows where the agent fails and how often.
- Same FDE title, very different job: five tests for spotting the impostor roles in a job posting
FDE job postings are multiplying fast, and the title no longer tells you what you will actually do. To find out, read how the company measures success and where the code you write ends up.
Prepare
- Alex Xu's System Design Interview: keep the four-step framework, add the AI layer yourself
The most useful part of this system design interview book is not its 30 sample designs. It is the four-step answer framework, and FDE candidates should treat it as a guide to their first working session with a client.
- Educative's FDE course aims squarely at the interview loop, but only for engineers who have already built AI systems
The syllabus puts the first question you ask a customer ahead of the first design you draw. Candidates who prepare mainly with LeetCode tend to skip that step.
The offer
- FDE salary: what job posts actually pay
Posted base-pay ranges from US job posts, by seniority, company and city. Updated daily.
- Three job postings, one ladder: FDE pay from one year of experience to eight
The distance between "1+ years of experience" in a Palantir posting and "2+ years managing FDEs" in an OpenAI one says more about the profession than any salary report.
- The $550,000 FDE figure is annual total compensation at two leading AI labs, not a monthly salary
The median base salary in US forward deployed engineer job postings is about $190,000 a year. The $550,000 figure is the top of an estimate of total compensation at OpenAI and Anthropic. Most of the difference is equity, which pays out slowly and is hard to value.