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

Design and build Docker’s AI Gateway, including model and tool routing, MCP services, control-plane infrastructure, secure credential management, policy enforcement, observability, caching, rate limiting, and agent evaluation systems. Lead architectural decisions, optimize performance and reliability at scale, guide roadmap planning, and mentor engineers while creating developer-facing APIs for AI applications.

Lead the architecture and implementation of Docker’s AI Gateway, including model and tool routing, MCP, control-plane systems, credential vaulting, policy enforcement, observability, analytics, caching, and rate limiting. Solve complex distributed-systems problems, establish technical direction, improve infrastructure, mentor engineers, and shape product strategy. Build secure, scalable services supporting model orchestration, agent evaluation, replay, and enterprise-grade governance.

Build and deploy production solutions with strategic customers using Docker, containers, Kubernetes, enterprise integrations, and agentic AI technologies. Lead engagements from discovery and architecture through rollout, establish secure and governable AI adoption practices, mentor engineers, support technical escalations, influence product direction, and codify repeatable delivery standards. The role requires extensive customer-facing technical leadership, production coding, software supply chain security expertise, and up to 50% customer-site travel.

Own the strategy, roadmap, and execution of Docker’s AI Gateway, enabling secure model access for developer and enterprise AI agent workflows. Responsibilities include simplifying onboarding, shaping APIs and integrations, defining governance and access controls, managing model interoperability, optimizing routing and inference costs, and driving launches. The role partners with engineering, design, customers, security stakeholders, and inference providers.

Own the vision, roadmap, revenue, and outcomes for Docker’s core Sandbox platform. Partner with developers, customers, designers, engineers, and ecosystem partners to define and deliver valuable, usable products. Engage users, prioritize features, guide iterative development, analyze qualitative and quantitative data, and scale services. The role requires technical knowledge of developer tools, AI agents, software supply chains, security, and sandboxed environments, along with strong communication and cross-functional leadership.

Build and operate production AI-powered developer tools, including code review assistants, test generators, deployment diagnostics, and incident-response agents. Develop the self-service platform supporting deployment pipelines, observability, security, cost management, and reliable AI systems. Integrate LLM providers, agent frameworks, MCP servers, CI/CD, and infrastructure platforms. Own features from design through production, participate in on-call, improve operational practices, collaborate cross-functionally, and mentor engineers.

Set technical direction for AI-powered developer tools and a self-service AI platform. Design, build, and operate production AI agents, scalable distributed systems, deployment frameworks, observability integrations, security controls, and CI/CD integrations. Establish LLM and agent-development standards, lead cross-team initiatives, mentor engineers, conduct design reviews, measure AI-tool effectiveness, and participate in on-call operations.

Partners with Marketing, G&A, and Product leaders on organizational design, workforce planning, talent management, performance, compensation, engagement, employee relations, and leadership effectiveness. Coaches managers, advises on complex employee matters, supports global teams, uses people data to identify trends, and coordinates with internal People, Legal, Finance, and Talent Acquisition teams.

Build and maintain an internal application framework with authentication, hosting, CI/CD, observability, and alerting defaults. Develop custom tools such as Slack bots, web applications, and workflows for business teams. Evaluate build-versus-buy decisions, integrate SaaS products and APIs, and own projects from scoping through adoption. Partner with engineering and non-engineering stakeholders while applying AI-assisted development and automation.

Leads Docker’s Forward Deployed Engineering program by defining delivery standards, quality metrics, operating rhythms, and engagement processes. Tracks customer and engineering commitments, manages dependencies and capacity planning, surfaces risks, communicates with executives, improves cross-functional collaboration, and mentors junior technical program managers. The role supports enterprise customers and requires strong knowledge of cloud platforms, containers, software delivery, and metrics-driven program management.