10 Vellum Software Engineer (New Grad) Interview Questions (2026)
Vellum's new-grad SWE loop in 2026 is a recruiter screen, one technical phone screen, and three to four virtual onsite rounds. The company builds developer tooling for evaluating, prompting, and deploying large language models — interviews favor candidates with full-stack instincts and a clear DX mindset.
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Loop overview
New-grad candidates report a 4-6 week timeline in 2026. Phone screen is 60 minutes coding. Onsite is one coding round, one frontend-or-backend product-build round, one technical deep-dive, and one behavioral. The team is small; new grads ship things end-to-end.
Behavioral (3)
Why Vellum? What about LLM developer tooling interests you?
Frequently askedOutline
Talk about a concrete LLM dev-experience pain point you've felt — prompt versioning, eval flakiness, deploying changes without breaking production. The company addresses these problems; show you've felt them. Specific stories from class projects or side projects help. Avoid generic 'I love LLMs'.
Tell me about a time you shipped a feature that a real user used.
Frequently askedOutline
STAR. Even a small audience (a class project that got picked up by a TA, a side tool used by friends) counts. Cover what users said, what surprised you, and what you'd change. Vellum engineers ship developer tools; user empathy for developers matters.
Tell me about a time you had to make a quick decision without all the data.
Occasionally askedOutline
STAR. Pick a concrete moment where waiting wasn't an option. Cover what was unknown, what you used to make the call, the result, and what you'd do differently. Show that you can act under uncertainty without freezing.
Coding (LeetCode patterns) (2)
Given a binary tree, return the right-side view (the values you'd see from the right).
Frequently askedOutline
BFS with level tracking — at each level, record the last node visited. O(n) time, O(n) space. Alternative: DFS prioritizing right child first, with a 'seen depth' check. Walk through a small tree where left subtree is taller.
Implement a function that returns whether a Sudoku board is valid.
Occasionally askedOutline
Three sets per row, column, and 3x3 box. Walk every cell. If non-empty, check it's not already in the row/column/box sets; insert it. Return false on collision. O(1) since the board is fixed-size. Walk through edge cases: empty board (valid), full board (need to verify all cells).
Technical (4)
Build a small interface that lets the user enter a prompt, send it to a backend, and stream the response token-by-token. (timed exercise).
Frequently askedOutline
Frontend: textarea + send button + streaming output area. Backend: route that returns a chunked or server-sent-events stream. Wire fetch with a ReadableStream reader (or EventSource) and append chunks to the DOM as they arrive. Discuss cancellation (AbortController) and error states. Show clean state management.
Implement a function that, given two prompts and their outputs, computes a 'similarity' score using cosine on bag-of-words.
Frequently askedOutline
Tokenize each output. Build count vectors over the union vocabulary. Compute dot product / (norm_a * norm_b). O(total tokens + vocab). Discuss the limitations (synonyms, paraphrases) and when you'd reach for embeddings instead. Walk through a small example.
Given a list of test cases with expected outputs and a model's actual outputs, design a metric that scores the model.
Frequently askedOutline
Multi-axis: exact match (strict), fuzzy match (token overlap, edit distance), semantic match (embedding cosine), or a learned judge (model-graded). Discuss each method's failure modes and when you'd combine them. Mention the importance of having a baseline.
Given a list of running model API requests and their start times, write a function that returns the average end-to-end latency per minute.
Occasionally askedOutline
Group requests by minute bucket of their end_time. Per bucket: sum (end - start) / count. O(n). Discuss handling open requests (still in flight), what to do for empty minutes (zero or null), and the streaming variant where requests arrive out of order.
System / object-oriented design (1)
Design a system that lets users version their prompts and roll back to a previous version atomically.
Occasionally askedOutline
Append-only version log per prompt. Each version has an immutable ID, the prompt content, and metadata. 'Active' pointer per prompt points to a version ID. Rollback updates the pointer. Discuss: branching, A/B comparison between versions, and how to surface diffs cleanly. Mention immutability for audit trails.
Vellum interview tips
- Full-stack literacy is real. Even if you have a backend background, expect a frontend-flavored exercise. Brush up on stream handling, state management, and async UI patterns.
- Developer-experience thinking is the company's product. Be ready to critique a developer-tool API or CLI and explain how you'd change it.
- Eval-and-versioning patterns come up often. Know what an evaluation harness does, why version pinning matters, and how rollback works.
- Coding rounds skew medium with strong emphasis on shipping working code in the time given. Pace matters; don't over-think.
- The team is small. Behavioral rounds favor engineers who can ship without a tech lead in the room. Have stories ready about owning ambiguity.
Frequently asked questions
How long is Vellum's SWE new-grad interview process in 2026?
Most reports show 4-6 weeks from recruiter outreach to offer. Onsite scheduling is usually quick once the phone screen passes.
Is Vellum remote-friendly for new-grad engineers?
Hybrid in San Francisco is the default expectation. Some teams accept fully remote. Confirm with your recruiter.
Does Vellum ask system design for new-grad SWE?
Yes — lightweight, usually around developer-tooling problems (prompt versioning, evaluation harnesses, deployment pipelines) rather than generic web-scale distributed-systems design.
What programming languages does Vellum use?
TypeScript and Python are the most common. Pick what you're fastest in for the coding rounds. Frontend rounds default to React + TypeScript.
Do I need ML knowledge to interview at Vellum as a new-grad SWE?
Conceptual familiarity with LLMs (you've used one, you know what prompting and tokens are) is enough. Deep ML expertise isn't required; the engineering side of developer tooling dominates.
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