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

The Head of Engineering, Platform will manage the engineering execution from architecture to delivery, focusing on improving AI workflows and team efficiency, while ensuring quality and reliability.

Own end-to-end engineering for a product domain, drive large latency improvements, build observability and model-selection systems, lead execution rituals, translate product goals into deliverables, operationalize continuous quality evaluation, and enforce engineering best practices to ensure reliability and scalability.

Lead and scale the iOS mobile platform end-to-end: own architecture, roadmap, delivery, and reliability. Drive major performance and crash-rate improvements, build observability and automated testing, coordinate closely with Product/Design/Backend, and improve EHR integrations and technical debt while establishing mobile engineering processes and execution cadence.

Lead integration strategy and deliver production-ready EHR and partner integrations. Work with customers to gather requirements, collaborate with AI/ML teams to bridge applied GenAI systems, and ship SDKs, proxies, and automation to improve reliability and reusability.

Own ARR for enterprise healthcare accounts by running high-velocity demos, negotiating and closing contracts, building pipeline at events, partnering with product/engineering, and continuously improving sales process and messaging.

Lead technical project delivery by building governance, defining sprint cadence and delivery standards, optimizing CI/CD pipelines, translating technical milestones for stakeholders, and creating repeatable engineering playbooks.

Own strategic enterprise clients, build executive trust, ensure measurable ROI and adoption, drive expansion, create playbooks, and surface client feedback to influence product roadmap.

Lead a specific AI Agent product end-to-end: define strategy, guide discovery, design, and delivery; partner with Engineering, Data Science, Sales, and Marketing; translate customer feedback into high-impact features; scale products through rapid experimentation and iteration to drive adoption and measurable healthcare outcomes.

Build and scale core research infrastructure and agentic systems across backend, frontend, and model integrations. Own reliability, observability, and performance; ship research-proven features to production rapidly and develop shared tools and SDKs to accelerate Research, QA, and Engineering.

Design scalable systems and playbooks to turn traction into repeatable execution. Partner with product and engineering to translate clinician pain into workflows, shape AI agent behavior to clinical quality standards, and iterate rapidly with customer feedback.