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

Lead and scale a Forward Deployed Engineering team embedding with enterprise customers to build production-grade AI-native workflows. Own delivery quality, stakeholder relationships, scoping, executive technical sponsorship, deal strategy, hiring, coaching, and partner enablement to ensure fast, repeatable, high-impact engagements.

Build and own enterprise-grade organization management, RBAC/authorization, audit logging, enterprise policies, admin APIs, and compliance features. Design scalable, secure multi-tenant platform primitives and tooling to support large organizations.

Lead the Desktop team building Cursor's desktop client: own UI, core features, and client-side architecture. Partner with product, design, and platform to deliver high-performance, reliable developer experiences. Hire and grow fullstack engineering talent, set engineering standards, and drive cross-cutting features like async agents, local↔cloud workflows, and deep product integration.

Embed with customer engineering teams to discover bottlenecks, design and ship Cursor-powered AI-native workflows end-to-end, ensure production reliability, monitor and iterate, and push reusable patterns back to the core product.

Build distributed training, inference, and RL infrastructure; create libraries for large-scale data jobs; architect systems converting user data into training data; collaborate with researchers to accelerate iteration and reproducibility.

Senior HR Business Partner supporting Finance, Legal, Marketing, Operations, and People. Acts as strategic advisor and hands-on builder to drive org design, talent strategy, performance management, leadership coaching, employee experience, and scalable People infrastructure while navigating high-stakes decisions and rapid growth.

Design and build core client infrastructure for Cursor's desktop app (macOS/Windows/Linux). Work on build/distribution systems, performance, reliability, instrumentation, telemetry, and internal tooling to enable fast, safe shipping of updates.

Build and improve large-scale GPU compute, storage, and software infrastructure to support training of agentic coding models. Work with ML researchers, cloud/OEM partners to design GPU clusters, improve training throughput, reliability, scheduling, data movement, automation, and developer experience across cloud and bare-metal environments.

Lead go-to-market strategy and positioning for developer-focused AI product features. Own launches, craft developer-facing content, enable GTM, run growth experiments, and capture customer and competitive insights to influence product and marketing.

Lead and grow an infrastructure engineering team that builds and operates cloud, networking, storage, and compute platforms. Own Kubernetes clusters, geo-deployment strategy, edge/security and CDN/WAF, storage systems (Postgres/OLAP/ClickHouse), cost optimization, and a unified container orchestration platform while hiring, mentoring, and contributing code.