Lead Platform Engineer
Summary
Lead Platform Engineer owning architecture, security, and scaling of a data infrastructure platform that turns scientific data into a queryable knowledge base. Day-to-day: building ingestion pipelines, microservices, and knowledge graph/vector search in Go and Python, plus managing cloud infra, CI/CD, and mentoring the platform team. On-site in San Francisco.
About the Role
Lead platform engineering for a data infrastructure company, building the foundational systems that turn diverse scientific data into a reliable, queryable knowledge base. You will set architectural direction, strengthen security and engineering practices, and help grow the platform team.
What You'll Do
Own the architecture, delivery, security, and scaling of the core data and execution platform.
Build and operate ingestion pipelines, APIs, microservices, and storage that normalize varied scientific inputs while preserving data provenance.
Manage knowledge graph and vector search systems to support combined structured and semantic retrieval.
Develop high-concurrency platform services in Go and Python, including controlled agent write access and isolated execution environments.
Set security boundaries for authentication, tenant isolation, secrets, encryption, and zero-trust access.
Own cloud infrastructure, CI/CD, and observability, and establish service objectives and reusable developer workflows.
Set engineering standards through architecture guidance, code reviews, mentoring, and team building.
Partner with company leadership on team design, interviewing, and platform engineering recruitment.
What We're Looking For
At least 5 years of platform or infrastructure engineering experience, with a track record building and operating production backend infrastructure, data platforms, or distributed systems.
Dedicated infrastructure engineering experience in addition to software engineering.
Strong experience with Kubernetes, Terraform, Ansible, and modern CI/CD systems.
Experience designing ingestion for messy, multi-source data, including schema harmonization and entity resolution.
Proficiency with Go, Python, FastAPI, TypeDB/TypeQL, Qdrant, GitHub Actions, OpenTelemetry, and Prometheus.
Experience with computational biology, biotech data systems, or compliance frameworks such as SOC 2 is a plus.
Compensation & Benefits
Base salary: $220,000 to $300,000 annually. Visa sponsorship or transfer is not available.
Location
On-site, five days per week in San Francisco, California. Relocation assistance is available.
Skills
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