Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
Build and operate LLM evaluation and batch-analysis pipelines
Own traditional ML workflows from data to scheduled production inference
Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

7+ years building and operating production backend systems, with strong general-purpose programming skills (we work primarily in Python)
Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
Hands-on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data

Senior Software Engineer – Applied AI

Key skills