Palantir Senior Software Engineer Interview Experience — Deep Dive on LLM Agent and Tool-Calling Design

Background

I have spent most of my career in systems-heavy engineering: real-time software, autonomy, and multi-agent architectures built around LLMs. In the stretch before this interview I was putting together agent systems that combine retrieval, tool orchestration and structured reasoning across messy, complicated data. My work lives where software engineering and applied AI overlap, and there, getting correct results, keeping latency low and staying reliable matter every bit as much as the quality of the model.

How I Prepared

What worked well

I deliberately prepared with a systems focus and a clear structure.

1. For system design, I used a step-by-step delivery framework as my backbone. Having it meant I stayed organized even when a prompt was vague or the conversation changed course midway.

2. I quit treating AI as only a matter of models and concentrated on autonomy and agents, meaning:

   • agents driven by LLMs
   • how tools get called and orchestrated
   • schemas and structured inputs and outputs
   • workflows triggered by events
   • running things safely, with validation

This line of thinking matched the problems Palantir deals with quite closely.

3. Rather than skim everything, I picked a handful of areas and went deep:
   • designing systems under real-world constraints
   • how agents talk to tools (MCP-style patterns, for instance)
   • tradeoffs in real-time systems where safety is critical

In the end, that depth counted for a lot more than covering everything.

What mattered less

Rehearsing and polishing answers ahead of time. Reasoning clearly and being candid about tradeoffs was worth much more.

What the Interview Process Was Like

Early rounds

My first technical interviews touched coding fundamentals, data structures and low-level design. The people interviewing me paid attention to my thought process rather than only the final answer being "right", and they welcomed me walking through my assumptions, edge cases and tradeoffs aloud.

System design round

One of the system design sessions dug far deeper than I had anticipated. The topics were LLM-driven agent systems, how tools are registered and found, whether to define a schema up front or validate at runtime, the boundary between a backend and an agent, and ways to execute actions safely. There was no wide architecture to sketch. Almost the whole session went into taking one design apart piece by piece. The interviewer was plainly checking whether I had really built something like it, and shallow familiarity would not have held up.

Advice for Other Candidates

1. Palantir cares a great deal about systems thinking, staying composed when requirements are fuzzy, real-world constraints, and ownership plus judgment. Only grinding LeetCode will not get you there.

2. Rehearse talking through systems out loud. Know why you went with a particular design, what you would build first and what could wait, and how you would balance latency, safety and scalability. The way you explain things counts as much as the solution itself.

3. State your assumptions openly and ask clarifying questions.

4. Going deep is better than going broad. If you have built a real system, particularly one involving agents, autonomy or heavy orchestration, build your answers around it. That is what makes you stand out.

Final Thoughts

I found this to be among the most absorbing interview loops I have done. Strong system design, frank tradeoff conversations and hands-on experience with complex systems all paid off. To anyone getting ready for it, best of luck, and try to enjoy the ride.