Senior Backend Engineer — growth-stage SaaS
Work context observed
90-minute live session: design, implement and debug a subscription-event processing system (webhook ingestion, idempotency, retry policy, billing-state reconciliation) against a seeded codebase with two planted defects. AI tools permitted and observed throughout.
Evidence by dimension
Problem framing
Strong evidenceAsked about delivery guarantees and duplicate-event volume before writing anything; explicitly narrowed scope to at-least-once delivery with idempotent consumers.
Architecture & trade-offs
Strong evidenceProposed queue-backed ingestion with an outbox pattern; articulated the cost of exactly-once claims and chose verifiable idempotency instead. Compared Redis- vs DB-backed dedup with concrete failure scenarios.
Debugging under pressure
Strong evidenceFound both planted defects (a race on subscription-state update; a swallowed exception in the retry path) in 31 minutes, narrating hypotheses and eliminating them with logs rather than guesswork.
Use of AI tooling — judgment & verification
Strong evidenceUsed an assistant to draft the reconciliation query, then caught its incorrect join condition by testing against the seeded edge case before accepting it.
Edge-case & correctness discipline
Moderate evidenceHandled clock-skew and out-of-order events when prompted, but did not raise them unprompted. Evaluator note: consistent once surfaced; recommend probing in the team interview.
Communication of decisions
Strong evidenceKept a running decision log unprompted; final walkthrough was ordered, complete, and honest about the shortcut taken on metrics emission.
Evaluator provenance
- 9 years backend (payments & subscription systems)
- Calibration: 96% agreement on benchmark set (n=14)
- Conflicts declared: none (no referral relationship)
- This session second-scored: yes — agreement on 5/6 dimensions
Artifacts attached
- Session recording (candidate-consented)
- Final code diff + decision log
- Structured scorecard (rubric v2.3)
- Second-scorer notes
Candidate response
Sharing & consent
- Owned by the candidate; shared per-employer with explicit approval
- Current-employer category blocked from discovery by candidate setting
- No personality, emotion or protected-characteristic inference — by policy, ever
- Correction & appeal: factual-error challenge with human review
- Retention: deleted on candidate request; auto-review at 24 months