Job Description
What You’ll Do
\n
•Define the technical direction for a critical domain: either (a) the AI platform layer (orchestration, evaluation, multi-model routing, hallucination mitigation) or (b) the consumer product + data layer (aggregation, enrichment, real-time sync, dynamic UI generation).
\n
•Make architecture decisions that affect the entire engineering team. Own technical RFCs. Set the quality bar.
\n
•Be the technical peer to our CTO in your domain. Push back when you disagree. Drive technical clarity.
\n
•Recruit. The best staff engineers attract senior engineers. Bring your network. Be the person others want to work with.
\n
•Ship code. This is not an advisory role. You write code, review code, and debug production issues.
\n
\n
\n What We’re Looking Fo
\n
r•8+ years of production engineering with 3+ years at senior/staff level influencing system-wide technical decisions
\n
.•Have built and owned at least one large-scale distributed system (10M+ users, sub-second latency, multi-service)
\n
.•Deep expertise in either: (a) AI/ML systems (LLM serving, evaluation frameworks, agent runtimes, RAG at scale) or (b) high-scale data infrastructure (real-time aggregation, streaming, event-driven architecture)
\n
.•Extreme AI fluency. Not just using tools — has strong opinions about model architectures, evaluation methodologies, and where the AI capability curve is heading
\n
.•Technical leadership through influence, not authority. Can get senior engineers aligned on an approach through clarity and evidence
\n
.•Preferred: Startup experience. Deep open-source contributions or significant published technical work
\n
.