Palantir interview
Forward Deployed Software Engineer (FDSE, incl. US Government and New Grad) · Deployment Strategist · Forward Deployed Infrastructure Engineer (FDIE) · Forward Deployed AI Engineer
Process
Recruiter screen
~30-min phone call. Assesses: Background walk-through, why Palantir, why the FDSE track specifically. [9][8][1]
Online assessment (some candidates, notably new grad)
HackerRank, three parts: SQL, an API-calling task, one algorithm problem. Assesses: Practical coding and data skills before any live round. [10][1]
Technical screen
Live, roughly 30-60 min with an engineer (HackerRank/CodePair; Karat reported in London 2021). Several 2024-2026 reports pair a coding task with a short decomposition/design prompt. Assesses: LeetCode-medium-style coding with clean code, plus first look at how you break down an open problem. [9][13][6][11][15]
Onsite: Decomposition
~60 min, little or no code; open-ended real-world problem, sometimes with a described database. Assesses: Splitting a vague problem into subproblems, scoping, data modelling, trade-offs, end-user focus. Some candidates get two decomposition rounds. [1][13][11][14]
Onsite: Learning
~60 min; interviewer teaches or hands over an unfamiliar concept, library, language, or query syntax, then you apply it. Assesses: Speed of learning, quality of clarifying questions without needing hand-holding. Several candidates say SQL appeared here. [1][6][10][11][13]
Onsite: Re-engineering / debugging
~60 min in an unfamiliar codebase (CodePair); find and fix bugs or extend the app. Assesses: Systematic code reading, hypothesis-driven debugging, verifying the fix. [1][7][4]
Onsite: Coding and/or system design
~60 min each; coding in CodePair often with ~15-20 min of embedded behavioral questions. Assesses: Clean working code, complexity awareness; for design, scaling, data stores, failure handling. [1][7][13]
Hiring manager
~60 min; may include past-project deep dive and another decomposition problem. Assesses: Probes the weakest area flagged earlier; final decision and team placement. [1][13][3][14]
Deployment Strategist track (variant)
Motivation screen -> technical round in a new SQL-like query language -> decomposition -> hiring manager; a Foundry/AIP build take-home reported recently but not universal. Assesses: Motivation and product familiarity, data fluency and recovery from correction, structured problem breakdown down to metrics, data, query, and pilot. [3][2]
FDIE track (third-party description only)
Recruiter screen (clearance, production ownership) -> technical phone screen -> deployment/troubleshooting scenario -> virtual onsite -> hiring manager. Assesses: Infrastructure, networking and live troubleshooting; fit for customer-facing ops. US Government postings require clearance or eligibility. [16][17]
AI tools in interviews: No Palantir-published statement on candidate AI use was found. An Exponent/Aced guide asserts that Palantir prohibits AI use throughout its interviews but cites no Palantir document; treat as unverified. [1]
Questions
Decomposition 10
Design a product that uses historical taxi-trip data to help drivers.
Build something that gathers data about life on a planet.
Third-party guide S1 lists a similar prompt: catalog species while exploring an unfamiliar environment
Design a system for internal company teams to organize meetups around hobbies, then code one core feature.
Approximate year; candidate says interview was about two years before a 2026 post
Given a vague real-world problem and a described database, design an application.
Feedback: should have split into subproblems first
Phone screen: discuss a decomposition design, then code a feature linking employees by shared interests.
Only the public overview of this post is readable; details are behind a login. Year approximate
Break down a large ambiguous problem: problem statement, metrics, root causes, datasets and joins, a test query, and a pilot.
Improve the New York City subway, or decide where to build new lines.
Guide attributes practice prompts to a Palantir interviewer; not a verified candidate report
Detect money laundering or fraudulent tax returns.
Same attribution caveat as above
Design a sync system between two employee record systems.
Guide labels samples as reported by candidates without individual citations
Design an application that lets users share their interests.
System design 2
Design Yelp, then extend the design as the interviewer adds complexity.
Design an air-gapped deployment architecture.
Same caveat as above
Coding 9
Given a set of jobs with dependencies, return a valid order to execute them.
Topological-sort style; a similar problem is reported in S13
Given a set of users, determine which one is the most active.
Using documentation for an obscure programming language, solve a set of problems with it.
Candidate attributes rejection to asking questions that signalled too much hand-holding
How would you optimize a given scheduling system?
Integrate an unfamiliar library into an existing system within a few minutes.
Solve a problem about playing a unique card game.
Implement search(user_id, users) for the interest-sharing application.
How would you make meeting-history lookups faster?
How would you speed up searching interests if the data must remain an array?
Take-home 1
Online assessment with one SQL task, one API-call task and one algorithm problem.
Debugging 4
Find and fix the defect that causes duplicate alerts to fire.
Debug a broken API service: trace logs, find bottlenecks, fix memory leaks.
Find and fix a double-counting bug in a HashMap-based tallying function.
Debug a program modelling infection spread across a social graph.
Customer scenario 1
Explain why your proposed solution needs to be built and what changes for the user if it works.
SQL and data 3
Work a decomposition problem that required learning and writing SQL during the interview.
Write specific SQL queries with no way to execute them.
Candidate was told no preparation was needed; failed this round
Using a new object-oriented query language, solve a data problem and explain each step.
Interviewer corrected mistakes live and asked for fixes
Domain 1
How would you troubleshoot a Palantir deployment that is running slowly?
CleverPrep question pattern; mixes candidate reports and editorial synthesis without separating them
Behavioral 4
Describe the most ambiguous project you have owned.
Tell me about a time you worked with unclear customer requirements.
What are you weakest at that could stop you succeeding here, and how would you handle it with a customer?
Walk through your internship project in detail. What did you enjoy most and least?
Motivation 3
Why do you want to be an FDSE specifically, and why Palantir?
Also reported in S18 and S9
Why Palantir, what do you know about what we actually build, and what do you believe in?
Why this company, why the government domain, and why the FDSE role?
Tips from the sources
- In decomposition, explicitly split the problem into subproblems and solve each before assembling the full design; a candidate's feedback flagged skipping this step. [13]
- Do not second-guess a correct solution without evidence; one candidate's hesitation on a topological-sort problem read as feigned difficulty. [13]
- In the learning round ask high-level clarifying questions; questions that suggest you need step-by-step guidance can sink the round. [6]
- Take clear positions in design rounds and defend them; a working solution beats an unfinished optimized one. [6]
- Prepare SQL and decomposition, not just algorithms; coding rounds stressed object structure and clean code more than algorithms. [5]
- SQL can appear in the learning round even for candidates told no preparation is needed. [11]
- Treat decomposition differently from a system design interview, but know system design concepts. [12]
- Practice reading unfamiliar code and debugging under time pressure, and tie every decision to the customer outcome. [4]
- Deployment Strategist: decomposition is not a consulting case; drive toward metrics, data sources, a test query and a pilot. [3]
- Use Foundry before interviewing (a free AIP Developer Tier exists); treating the company as a black box reads poorly. [3][2]
- Narrate each step during the query-language round and absorb corrections without repeating the mistake. [3]
- Casual conversations during the process are evaluative too. [3]
- Expect a possible multi-week wait after the hiring manager round. [14]
- Ask for a referral if you can; one candidate who applied cold regretted not doing so. [13]
Not found in public sources: No Palantir-published description of the loop could be read: the employee-advice post at blog.palantir.com ('Interviewing at Palantir: advice from Palantirians') returned 403 to our fetcher, and palantir.com/careers renders no process text; Lever postings describe no stages. No employer statement on AI use in interviews. FDIE has no first-hand candidate report (only CleverPrep synthesis). Reddit threads were not fetchable. Decomposition and learning details vary widely by year and team; Taro/Exponent/PracHub reports are anonymous and unverified. Forward Deployed AI Engineer (AIP) loop: no role-specific report found.
Sources
- Palantir Forward Deployed Engineer Interview Guide. Exponent (now aced.io), 2026. Third-party guide
- Palantir Deployment Strategist Interview Guide. Exponent (now aced.io), 2026. Third-party guide
- Palantir Deployment Strategist interview experience. Exponent (now aced.io), anonymous candidate, 2026. Candidate report
- Palantir Forward Deployed Engineer (L4) interview experience. Exponent (now aced.io), anonymous candidate, 2026-09. Candidate report
- Palantir FDSE (Gov) entry-level interview experience. Exponent (now aced.io), anonymous candidate, 2026-08. Candidate report
- Palantir Forward Deployed Engineer interview experience (FDSE Commercial). Exponent (now aced.io), anonymous candidate, 2026. Candidate report
- Palantir FDSE Denver, accepted offer. Taro, anonymous candidate, 2025-03. Candidate report
- Palantir FDSE New York, no offer. Taro, anonymous candidate, 2025-08. Candidate report
- Palantir FDSE New Grad, no offer. Taro, anonymous candidate, 2024-11. Candidate report
- Palantir FDSE New Grad Washington, no offer. Taro, anonymous candidate, 2023-10. Candidate report
- Palantir FDSE US, no offer (negative). Taro, anonymous candidate, 2025-11. Candidate report
- Palantir FDSE US, no offer. Taro, anonymous candidate, 2025-10. Candidate report
- Interview Experience: Palantir. Priydarshi Singh (dryairship), personal blog, 2022. Candidate report
- Palantir Forward-Deployed Engineer interview: referral, decomposition, and long decision wait. PracHub, anonymous candidate (platform-edited), 2026-09. Candidate report
- Palantir FDSE Tech Phone Screen: Decomposition Design and Coding Interview. 1point3acres, anonymous candidate, 2025. Candidate report
- Palantir Forward Deployed Infrastructure Engineer interview guide. CleverPrep, 2026-09. Third-party guide
- Forward Deployed Infrastructure Engineer - US Government (Washington, D.C.). Palantir (Lever posting), 2026. Employer-published
- Palantir FDSE US, no offer (headcount filled). Taro, anonymous candidate, 2025-11. Candidate report
- Palantir FDSE Interview Experience (REJECTION~). Reddit r/csMajors, 2025. Candidate report
- Palantir FDSE Full Interview Loop Process. u/Not_the_Sauron, Reddit r/csMajors, 2025. Candidate report