Palantir Senior Software Engineer Interview Questions

1.Tell me about a project where you were handed a vague problem with no clear requirements. How did you figure out what to actually build?

2.Tell me about a time you were racing against a hard deadline — something that actually couldn't slip. What did you cut, and how did you decide what to cut?

3.Tell me about a time you had to explain a genuinely complex technical system to someone — an executive, a customer, or a non-engineer — who needed to make a real decision based on your explanation. 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. How did you get up to speed, and what did you build?

5.Describe a situation where you were brought in midstream on a failing or stalled project with no clear owner and no clear path forward. What did you actually do first?

6.Walk me through a time when you were the technical lead on something that was breaking in production — not a minor bug, but something that was actively causing damage — and you couldn't immediately identify the root cause. How did you run that incident?

7.You're working with Conjure to define an API between two Foundry services. A junior engineer on your team asks why you'd use Conjure instead of just writing a REST API by hand. What do you tell them?

8.You have a Spark job that reads a large Parquet dataset in Foundry, does some transformations, and writes back out. It's been running fine, but after the dataset grew from 50GB to 500GB it started failing with out-of-memory errors on the executor nodes. Where do you start?

9.AIP needs to let enterprise customers run LLM queries against their operational data in Foundry — but with strict access controls so a user can only see data their role permits. How would you design the access control layer between the LLM and the underlying data?

10.Apollo has to deliver software updates to thousands of environments — some on AWS, some on-prem, some air-gapped with no internet access. How would you design the update delivery mechanism to handle the air-gapped case without breaking the rest of your pipeline?

11.You're building a multi-tenant data platform where different enterprise customers' data must be strictly isolated — same Kubernetes cluster, same microservices, but a bug cannot leak Customer A's data to Customer B. Walk me through how you'd architect that isolation.

12.You're designing Foundry's ontology layer — the abstraction that lets analysts query objects like 'Aircraft' or 'Transaction' without knowing which underlying databases they come from. The ontology needs to support real-time updates, historical point-in-time queries, and joins across object types backed by different storage systems. What are the hardest problems here and how do you approach them?

13.Gotham analysts often need to search across millions of entities — people, vehicles, locations — in near real-time. How would you design the search indexing layer to support fuzzy matching and cross-entity joins at that scale?

14.Foundry pipelines often have dozens of interdependent transforms — each one a node in a DAG that reads from upstream datasets and writes to downstream ones. How would you design the pipeline scheduler that decides which transforms to run, in what order, and when to re-run them after upstream data changes?

15.AIP lets users run LLM-powered workflows that take actions in the real world — submitting purchase orders, updating records, sending alerts. How would you design an audit log system for these agentic actions that satisfies both operational debugging needs and regulatory compliance requirements?

16.Apollo ships software updates to thousands of environments on different release cadences — some environments get daily updates, others are frozen for months at a time due to customer change control windows. How would you design the release targeting and rollout system that decides which environments get which version when?

17.Foundry needs to support a 'dataset lineage graph' — given any dataset, you can trace exactly which upstream sources it was derived from, through which transforms, going back potentially hundreds of hops. This graph has tens of millions of nodes and needs to support real-time lineage queries. How do you design the storage and query layer?

18.Palantir's enterprise customers need Foundry's data sync layer to replicate operational databases — think SAP ERP, Oracle, Salesforce — into Foundry in near real-time, with full change history and the ability to reconstruct any past state. How do you design this ingestion and change-data-capture pipeline?

19.Tell me about a time you pushed back on a senior engineer or architect's technical decision and turned out to be right. How did you make your case, and what happened after?

20.You've just joined a Palantir deployment team embedded with a new enterprise customer. Within a week, you realize their data team has deeply flawed mental models of what Foundry can actually do, and they've built a roadmap around those misconceptions. How do you handle that?

21.Tell me about a time you had to build alignment across multiple engineering teams who didn't report to you and had conflicting priorities. What was your actual approach, and where did it break down?

22.You're the senior engineer on a Foundry feature that customers love, but your team's consensus is that the underlying implementation is a slow-moving disaster — unmaintainable, unscalable, and increasingly hard to debug. How do you make the case for a rewrite, and how do you actually get it prioritized against the backlog of new features the business wants?

23.Tell me about a time you realized a technical decision you championed was causing real harm — to users, to your team, or to the system. How did you handle owning that publicly?

24.You're a senior engineer on a Palantir platform team and a Forward-Deployed Engineer in the field is asking you to make an exception to your API contract — they need a capability for a specific government customer that would require you to break an abstraction you've been careful to maintain. How do you think through that decision, and how do you make the call?

25.Estimate how many API calls Foundry's ontology layer handles per day across all enterprise customers. Walk me through your assumptions.

26.A Foundry customer's dataset — one that drives a live operational dashboard — suddenly shows a 40% drop in row count with no code changes and no pipeline failures. How do you diagnose it?

27.Estimate the annual infrastructure cost to Palantir of storing full historical change-data-capture logs for a single large enterprise customer running Foundry — assume they have 200 operational databases and 10TB of daily change volume.

28.AIP usage across enterprise customers has grown 3x in six months, but the number of workflows that actually reach production — rather than staying in pilot — hasn't grown at all. How would you diagnose why, and what levers would you pull?

29.Apollo manages software delivery to thousands of heterogeneous environments. If we told you that p99 deployment latency had silently doubled over the past quarter with no major code changes, how would you figure out why — and how confident could you actually be in the root cause?

30.Palantir has ~300 enterprise and government customers. If we wanted to forecast how much platform compute capacity we'd need in 18 months, how would you build that model — and where would it most likely be wrong?