Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Translate client scientific needs into product requirements, prioritize roadmaps with researchers and engineers, define success metrics, and drive cross-functional delivery of AI-powered life-science products while balancing feasibility and client expectations.

Design realistic biological benchmarks and curate high-quality datasets to evaluate and train AI systems; analyze model failures, iterate on data and evaluation criteria, collaborate with ML researchers, and manage workflows and documentation across domain experts.

Lead and execute growth strategy to drive adoption among scientists in academia and industry. Collaborate with science teams and partners to create demos, run go-to-market campaigns, build community, use data to optimize engagement, and translate market insights into product direction to ensure measurable scientific impact.

Lead backend-focused full-stack development for an AI-driven scientific discovery platform: design and maintain services, APIs, data pipelines, cloud infrastructure, CI/CD, observability, and frontend integrations; drive architecture, mentor engineers, and collaborate with research and design teams to deliver production-grade AI capabilities.

Design, build, and operate large-scale Kubernetes clusters and custom operators (CRDs) to orchestrate thousands of persistent AI agent workloads. Drive cluster scaling, autoscaling, scheduling, storage, networking, observability, and IaC. Troubleshoot distributed infrastructure, set best practices, and partner with backend, ML, and research teams to deliver a production-grade platform for long-running scientific workloads.

Build, deploy, and maintain production AI agents for scientific R&D. Work directly with customers to prototype, integrate, troubleshoot, and iterate on agent architectures, prompting, tooling, and evaluation to deliver measurable scientific and operational impact.

Design and implement performant, scalable front-end interfaces and data visualizations for a scientific discovery platform. Build a modular design system, optimize rendering and real-time data flows, and collaborate with product and research teams to translate scientific workflows into intuitive user experiences.

Drive revenue by prospecting, discovery, solutioning, negotiation, and closing biotech and academic customers. Partner with product and engineering to relay feedback, define ICP, messaging, pricing, and repeatable processes. Build trusted early-customer relationships and contribute to go-to-market strategy in an early-stage, ambiguous environment.