AI Engineer, Product

Embedded directly in a product team as search, chat, documents, or audio, you'll improve AI-powered features through rigorous evaluation, prompt and orchestration design, and rapid experimentation. You'll own your domain's AI quality end-to-end: define what 'good' looks like, measure it, run experiments, and ship what works. Work with Science to deliver measurable improvements to quality, latency, safety, and reliability.

Responsibilities

Design and run evaluations for your product area: reference tests, heuristics, model-graded checks tailored to search relevance, chat quality, document understanding, or audio performance; Define and track metrics that matter: task success, helpfulness, hallucination proxies, safety flags, latency, cost; Own prompt and orchestration design: write, test, and iterate on prompts and system prompts as a core part of your work; Run A/B tests on prompts, models, and configurations; analyze results; make rollout or rollback decisions from data; Set up observability for LLM calls: structured logging, tracing, dashboards, alerts; Operate model releases: canary and shadow traffic, sign-offs, SLO-based rollback criteria, regression detection; Improve core behaviors in your product area, whether that's memory policies, intent classification, routing, tool-call reliability, or retrieval quality; Create templates and documentation so other teams can author evals and ship safely; Partner with Science to diagnose regressions and lead post-mortems

Requirements

3-4 years of experience; backgrounds that fit well include ML engineers moving closer to product, or software engineers with real AI/ML production experience; Strong TypeScript or Python skills; Production LLM experience: prompts, tool/function calling, system prompts; Hands-on with evals and A/B testing: you can design metrics, not just run them; Comfortable implementing directly in product code, not only notebooks; Observability experience: logging, tracing, dashboards, alerting; Product mindset: form hypotheses, run experiments, interpret results, ship; Clear communication, autonomous, and oriented toward production impact over experimentation for its own sake

Nice to have

Safety systems experience: moderation, PII handling/redaction, guardrails; Release operations: canary/shadowing, automated rollbacks, experiment platforms; Prior work on search ranking, chat systems, document AI, or audio ML features

Benefits

comprehensive benefits package designed to support your well-being, growth, and work-life balance; healthcare coverage; parental leave; retirement plans; relocation support; wellness programs; meal and transportation allowances; other location-specific perks