Staff Software Engineer (Tech Lead)

About the Role

We are looking for an Technical Lead to own the architecture, execution, and evolution of our AI-driven platform. This is a senior, hands-on leadership role for someone who has built real systems with LLMs and understands how to take AI from prototype to production at scale.

This is not a pure management role. You’ll operate as a player-coach, writing production code, setting technical direction, and guiding a small, senior engineering team.

What You'll Do

• Own System Architecture: Design and evolve distributed systems on GCP (Cloud Run, Pub/Sub, BigQuery), making final decisions on service boundaries, data models, and technology trade-offs across Go, Python, and TypeScript.
• AI & LLM Strategy: Lead hands-on integration of AI systems, including open-source LLMs, embeddings, and speech models. Define prompt optimization, evaluation strategies, and safety practices using tools like LangFuse.
• Operational Excellence: Champion observability, reliability, and scale. Oversee event-driven ingestion and automated QA pipelines for call transcripts and healthcare data (FHIR / Medplum).
• Delivery & Execution: Contribute code to critical paths while leading major technical initiatives. Identify gaps, unblock teams, and drive projects to completion.
• Cross-Functional Leadership: Translate complex technical constraints into clear options and trade-offs for Product, Design, and Clinical Operations.

Who You Are

• 8+ years of software engineering experience, with 2+ years leading projects or serving as a Tech Lead.
• Staff-level scope or equivalent technical impact.
• Strong LLM experience in production environments (hands-on required).
• ML background preferred, especially applied machine learning or AI infrastructure.
• Expert-level proficiency in Go, Python, or TypeScript/Node, with the ability to review code across the stack.
• Deep experience with distributed systems, containerized deployments (Docker, Kubernetes, Cloud Run), and event-driven architectures.

Preferred

• Experience hosting or integrating open-source models (e.g., vLLM, Ollama), with a strong understanding of RAG architectures.
• Background in regulated environments (HIPAA, SOC 2) or healthcare data standards (FHIR, HL7).
• Strong written and verbal communication skills, including writing RFCs and explaining technical strategy to non-technical stakeholders.

Why You'll love it:

• High Ownership: Architect and lead AI systems that directly impact real users.
• Senior, Agile Team: Small group that ships fast, tests in production, and learns from failure.
• Flexible Bay Area Hybrid: In-person collaboration without rigid rules.
• Great Tools & Comp: M-series Macs, Linear, GitHub, GCP, competitive compensation, equity, and real perks.
• Career Growth: Opportunity to grow into an Engineering Manager role over time, if desired.