Palantir Software Engineer Interview Questions

1.Tell me about a time you were handed a project with almost no requirements. How did you figure out what to actually build?

2.Tell me about a time you had to ship something under a hard deadline that was genuinely at risk. Walk me through exactly what happened.

3.Describe the last time you had to explain something technically complex to someone non-technical — maybe a customer, an executive, or a business stakeholder. What was it, and how did you approach it?

4.Tell me about a time you had to ship something meaningful in a domain you knew almost nothing about going in — what was the domain, how did you ramp up, and what did you actually build?

5.Walk me through a time you were given a business problem with no clear technical solution defined. How did you go from 'here's the problem' to an actual design, and where did your first instinct turn out to be wrong?

6.Tell me about a time you were close to shipping something when a critical new constraint appeared — a security requirement, a compliance rule, a customer demand — and you had to absorb it without slipping the deadline. What did you do?

7.You're writing a code review for a teammate's TypeScript service that talks to a PostgreSQL database — you notice they're constructing SQL queries with string concatenation. What do you flag, and how do you frame the feedback?

8.You have a Python Spark job that processes a large Parquet dataset daily. It's been running fine for months, but today it's taking 3x longer with no obvious code change. What are the first five things you check?

9.You're building a GraphQL API in TypeScript that fronts a Foundry-style ontology — entities like 'Asset', 'Incident', and 'Workorder' with relationships between them. A client sends a deeply nested query that resolves five levels of relationships. How do you prevent this from taking down your service?

10.Apollo ships software to thousands of environments including air-gapped deployments that can't phone home. How would you design a feature flag system that works correctly in both connected and fully offline environments?

11.You're building the ingestion layer for a Foundry pipeline that receives security event logs from 50 different customer environments — each with a different schema, timestamps in different timezones, and field names that mean different things. How do you design this so downstream analysts can query across all of them?

12.Gotham is used by analysts who might be querying an object graph with millions of nodes — people, locations, events, and their connections. You need to implement a traversal that finds all entities within N hops of a seed entity, but it must return results in under 2 seconds for N up to 4. Walk me through your design.

13.Foundry's Ontology lets customers define objects like 'Patient' or 'Shipment' and link them together. How would you design the storage layer that backs an ontology with hundreds of object types, each with different schemas, and billions of total object instances?

14.AIP lets enterprise customers run LLM workflows against their sensitive operational data. How would you design an audit logging system that gives compliance teams a complete, tamper-evident record of every LLM query, what data it touched, and what it returned?

15.Apollo needs to deliver software updates to tens of thousands of environments simultaneously — including some that are fully air-gapped. Design a rollout orchestration system that can push a new version of Foundry to all environments while detecting and halting on regressions before they propagate globally.

16.Gotham analysts often define saved searches and alert rules — 'notify me when a new entity matching this pattern appears.' Design a system that evaluates these standing queries against a high-volume stream of incoming intelligence data in near real-time.

17.Foundry pipelines often chain together — the output of one transform is the input to the next, and a single source dataset might fan out to hundreds of downstream datasets. Design a dependency tracking and incremental computation system so that when a source dataset changes, only the affected downstream transforms re-run.

18.AIP needs to enforce fine-grained access control over which data objects an LLM can reference in its responses — different users have different clearances, and a model that 'knows' data from a restricted object must not leak it to an unauthorized user sharing the same session context. How do you design this enforcement layer?

19.Tell me about a time you disagreed with a technical decision your team had already committed to. How did you handle it?

20.Think about a piece of technical work you shipped that you're genuinely proud of. What's the one thing you'd change about it now?

21.Describe a time you had to get alignment from people outside your team to move a project forward. What did you actually do to get them on board?

22.Tell me about a time a project you were leading started to slip — scope crept, a dependency was late, or the technical complexity was higher than expected. How did you respond?

23.You've been handed ownership of a system that has no documentation, the original author has left, and production incidents keep happening. Walk me through the first two weeks.

24.Have you ever worked on something that had real ethical complexity — where the right thing to build wasn't obvious, or where the software could be used in ways you were uncomfortable with? How did you think through it?

25.Foundry has around 200 enterprise customers. Estimate how many Foundry pipeline transforms are executing across all of them on a typical weekday, and what that implies for our compute infrastructure.

26.An analyst on a Gotham deployment tells you the app feels 'slow' this week, but there's no incident, no spike in error rates, and nothing shipped. How do you figure out what changed?

27.AIP's usage has grown 40% quarter-over-quarter. Estimate what percentage of that growth is likely coming from net-new enterprise customers versus expansion within existing ones, and explain the business implications of each scenario.

28.You're a Forward-Deployed Engineer embedded at a large hospital network. They hand you a spreadsheet with 18 months of ICU patient data and say 'we want to predict which patients will need a ventilator in the next 12 hours.' Walk me through the first three days.

29.Estimate the total cost to Palantir of one hour of Foundry being completely unavailable for all commercial customers. Break it down by customer impact, internal cost, and reputational exposure.

30.Palantir's AIP boot camps convert skeptical enterprise buyers into paying customers in a few days. Design a metric framework that tells you, six months after a boot camp, whether it actually drove durable product adoption or just a one-time spike.