Senior AI Engineer — Inference & Agent Systems

About the role

The problems here don't have blog posts about them yet. Parallel agent DAG execution under hard latency budgets, streaming synthesis across partial sub-agent results, eval harnesses for non-deterministic multi-step systems: these are genuinely unsolved at production quality. Every engineer's decisions ship to production.

What you'll do

• Drive TTFT below 400ms for multi-step agent pipelines
• KV cache strategy, prompt compression, dynamic context window management
• Design and implement Plan-Execute-Synthesize pipelines that run sub-agents in parallel DAGs, not sequential chains
• Build reliable orchestration on top of Temporal: retries, timeouts, partial failure recovery, idempotency
• Own the eval framework end to end: ground truth datasets, automated scoring pipelines, regression detection on every PR

What you need

• Machine learning
• LLMs
• Python
• Kafka
• PostgreSQL
• Go
• Any graduate

Good to have

• Docker
• Regression testing
• Test cases