OpenAI Forward Deployed Engineer Interview Guide

The short answer: OpenAI publishes one interview guide for all roles and no FDE-specific loop. It describes a resume review, an introductory call, skills-based assessments that vary by team, and final interviews of 4 to 6 hours with 4 to 6 people. It also says some formats allow AI tools and others do not, and that your prep materials will say which. FDE candidate reports add a take-home case study, an AI-enabled coding screen, a project deep dive and a system design or customer round, though only a few reports exist and they disagree on the take-home format. Last reviewed October 2026.

OpenAI forward deployed engineer interview: quick answers

The OpenAI forward deployed engineer role

What OpenAI forward deployed engineers work on, the skills its job postings ask for, and what a week can look like. OpenAI posts the role as Forward Deployed Engineer (FDE), Forward Deployed Software Engineer.

OpenAI forward deployed engineer levels and pay

Your level sets the bar you are interviewed against and the pay band of the offer.

OpenAI does not publish FDE levels, and no FDE posting states one. The tables use posting titles: Forward Deployed Engineer asks for 5+ years and Forward Deployed Software Engineer for 7+ years of full-stack work.

Pay in OpenAI's US job postings

OpenAI's US postings list a salary range, and every FDE posting adds that the role offers equity. No posting states a level.

Every US Forward Deployed Engineer posting shares one $185K to $300K range, whatever the vertical or city. Forward Deployed Software Engineer ranges are wider and start lower outside San Francisco. The FDE manager posting is left out of the table. Ranges seen October 28, 2026.

OpenAI forward deployed engineer interview process

OpenAI's guide is general and says formats vary by team. The stages below follow that general process and add what FDE candidates report, which supplies the round detail and sometimes conflicts.

Based on OpenAI's own pages and candidate reports.

OpenAI says recruiting replies within about a week after each stage, and the decision follows within about a week of finals, sometimes after reference checks. One US FDE candidate said the whole process took about two weeks and felt more focused than a normal software engineer loop. Last reviewed October 2026.

What is different at OpenAI

• The FDE team partners with customers to turn research breakthroughs into production systems, working between customer delivery and core platform development. OpenAI measures success by production adoption, measurable workflow impact and eval-driven feedback that changes product and model roadmaps.
• OpenAI splits the field into several roles. Forward Deployed Engineers own discovery through production rollout. Forward Deployed Software Engineers are more build-focused, write full-stack software on OpenAI APIs and ask for 7+ years versus 5+. Deployment Leads own the delivery plan, sequencing and ROI and are not the hands-on engineers. Applied AI Engineers sit in Go To Market, Technical Success, outside the FDE department, and Applied AI Architects are presales with commission.
• Travel of up to 50 percent is required for FDE and FDSE roles, and the Gov role includes on-site work with customers. In a published interview, OpenAI's Global Head of FDE said about 50 percent on site is the guideline, with UAE and Japan teams around 80 percent and some US and Europe staff with customers 2 to 3 weeks a month.
• There are vertical FDE roles. Healthcare FDEs work with PHI and HIPAA safeguards and integrate with health records and claims systems. Others cover legal, financial services, government with a TS/SCI clearance, and AI infrastructure, where FDEs work on chip design, verification and inference performance with graders and benchmarks.
• The AI rule is set per interview. OpenAI added a paragraph to its guide between July and August 2026 saying some formats allow AI tools and others do not, and the prep materials say which. One FDE candidate reported a coding screen with AI enabled.
• On 2026-05-11 OpenAI launched the OpenAI Deployment Company, a majority-owned standalone unit that embeds FDEs in organizations, and agreed to acquire Tomoro to bring about 150 FDEs and deployment specialists. OpenAI says a typical engagement starts with a diagnostic, picks a few priority workflows, then designs, builds, tests and deploys production systems inside the customer.

OpenAI forward deployed engineer interview questions

Questions from our bank, then scoping, design, fundamentals and behavioral prompts we wrote for this guide around OpenAI's products and customers.

1from typing import List, Tuple
2
3def plan_batches(tokens: List[int], max_items: int, max_tokens: int, tpm: int) -> List[Tuple[int, List[int]]]:
4    """Return (send_second, document_indices) for each batch, in order."""
5    pass

1from collections import deque
2from typing import List, Tuple
3
4def plan_batches(tokens: List[int], max_items: int, max_tokens: int, tpm: int) -> List[Tuple[int, List[int]]]:
5    if max_items < 1 or max_tokens < 1 or tpm < 1:
6        raise ValueError("limits must be at least 1")
7    cap = min(max_tokens, tpm)
8    batches = []
9    cur, cur_tokens = [], 0
10    for i, n in enumerate(tokens):
11        if n < 0 or n > cap:
12            raise ValueError(f"document {i} cannot fit in a batch")
13        if cur and (len(cur) == max_items or cur_tokens + n > cap):
14            batches.append((cur, cur_tokens))
15            cur, cur_tokens = [], 0
16        cur.append(i)
17        cur_tokens += n
18    if cur:
19        batches.append((cur, cur_tokens))
20
21    window = deque()  # (second, tokens) for batches sent in the last 60 seconds
22    used = 0
23    t = 0
24    plan = []
25    for indices, size in batches:
26        while True:
27            while window and t - window[0][0] >= 60:
28                used -= window.popleft()[1]
29            if used + size <= tpm:
30                break
31            t = window[0][0] + 60  # wait until the oldest batch leaves the window
32        window.append((t, size))
33        used += size
34        plan.append((t, indices))
35    return plan
36
37# Complexity: O(n) time, since each batch enters and leaves the window once; O(n) space.

How to prepare

A plan for the OpenAI loop, most important first:

1. Build a small retrieval app on the OpenAI API end to end, with a working demo and a short design doc, so any reported take-home format feels familiar.
2. Practice walking through a design and explaining how it would change with new customer needs, since one candidate was told finals revisit the take-home.
3. Prepare a deep dive on the most complex project you have led, covering scale, evaluation and the decisions you made yourself.
4. Practice coding problems with an AI assistant on and off, stating time and memory complexity and checking every line it writes.
5. Practice open-ended customer scenarios that mix system design with scoping questions, evals and LLM trade-offs.
6. Read OpenAI's interview guide, the Charter and recent posts for your target team, and confirm the AI rule for each round.

Practice path

Courses that cover the rounds above:

• Forward Deployed Engineer Interview
• AI Agent System Design
• System Design
• Data Structures and Algorithms
• SQL