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

Lead software engineer responsible for designing, coding, testing, debugging, and stabilizing Java-based applications. Author and review technical designs, own complex stories and domain dependencies, mentor team members, enforce best practices, interact with business stakeholders, and improve processes and metrics. Provide guidance to contractors and participate in related agreements and SLAs.

Hands-on Tech Lead to design and deliver domain-driven Node.js/TypeScript microservices for customer-facing digital experiences. Own greenfield builds, set API standards, ensure production readiness (SLOs, observability, runbooks), lead incident triage/RCA, mentor engineers, and collaborate across web, mobile, data, security, and ops teams.

Lead delivery of a modern POS platform across UI, BFF, and backend microservices. Own product backlog, translate capabilities into user stories, define MVP scope and priorities, plan roadmaps, and support multi-squad delivery while partnering with architecture, store operations, and business stakeholders.

Customer-facing Forward Deployed Engineer who architects and delivers agentic AI POCs and enterprise deployments, mentors distributed teams, optimizes platform performance, and enforces MLOps/FinOps best practices.

Lead performance testing efforts: design and execute load tests, analyze results, perform root cause analysis, collaborate with developers and infrastructure to improve system performance, establish performance testing practices, create test artifacts, and generate management reports.

Design and own an end-to-end, agentic AI content generation platform using .NET and Azure. Architect event-driven agents, RAG pipelines with Azure OpenAI and Cognitive Search, integrate third-party and WordPress APIs, ensure multitenancy, security, observability, and CI/CD with IaC. Collaborate with DevOps to deliver scalable, auditable content automation.

Design, develop, deploy, and manage API proxies on Apigee Edge/X across on-prem, cloud (GCP), and hybrid environments. Implement Apigee policies for security, traffic management, caching, transformations, and error handling. Troubleshoot runtime issues, integrate with backend services, manage environments and keystores, participate in CI/CD, and maintain API documentation.

Design, build, and scale production Generative AI applications: multi-agent systems, advanced RAG pipelines, LLM integration and fine-tuning, scalable FastAPI backends, vector search, monitoring, and Dockerized deployments.

Own the AI use-case backlog and prioritize agent-assist scale-out. Translate business intent into Epics, Features, and User Stories with explicit acceptance criteria in Azure DevOps. Run sprint planning, refinement, reviews, and demos on a fast-paced AI-infused agile cadence. Leverage AI tooling to draft requirements, generate stories, and author acceptance criteria. Coordinate with stakeholders and transformation advisors to meet call reduction, AHT, and deflection targets.

Lead architecture, design, and delivery of large-scale microservices systems. Define standards, mentor teams, drive cloud, containerization, CI/CD, observability, data strategies, and risk mitigation while aligning technology with business goals.