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

Develop and maintain scalable Java and Spring Boot backend applications and REST APIs. Optimize CPU, memory, and overall application performance; identify bottlenecks; resolve production issues; and contribute to architecture, code reviews, reliability, and scalability. The role also involves Node.js or Python FastAPI services, cross-functional collaboration, and potential work with GraphQL, generative AI, cloud platforms, containers, CI/CD, and monitoring tools.

Design and implement enterprise AI architectures spanning GenAI, machine learning, RAG, agentic workflows, data pipelines, APIs, and production deployments. Build Python prototypes and AI services, define governance and evaluation frameworks, integrate models with enterprise platforms, and guide engineering teams through implementation. The role requires hands-on expertise with LLM applications, orchestration frameworks, model lifecycle management, monitoring, security, and scalable production AI systems, preferably in financial services.

Designs, builds, and operates scalable enterprise data platforms supporting ingestion, processing, storage, governance, analytics, and AI/ML. Responsibilities include developing batch and real-time pipelines, lakehouse and warehouse architectures, orchestration, infrastructure automation, CI/CD, monitoring, security, cost optimization, and observability. The role partners with data, ML, DevOps, security, and application teams, troubleshoots complex platform issues, establishes reusable engineering standards, contributes to architecture strategy, and mentors engineers.

Design end-to-end web and mobile experiences for enterprise tools and a B2C marketplace. Conduct user research and usability testing, create UX flows and high-fidelity interfaces in Figma, collaborate with Product and Engineering, and develop scalable component libraries and design systems. Balance user needs, business goals, and technical constraints while clearly communicating design decisions.

Systems Analyst bridging business and technology for an enterprise API integration platform. Responsibilities include gathering requirements, analyzing current and future processes, defining functional and technical specifications, supporting integration design, conducting gap analysis, assisting testing and UAT, monitoring performance, and supporting change management and deployment. The role requires collaboration with stakeholders, developers, and quality engineering teams to deliver reliable integration solutions.

Leads complex enterprise technology projects across business, product, and engineering teams. Responsibilities include project planning, roadmap development, risk and dependency management, delivery governance, release coordination, stakeholder communication, KPI tracking, resource and budget management, process improvement, and team coaching. The role promotes Agile and modern delivery practices while ensuring quality, execution accountability, and alignment with strategic business objectives.

Designs and maintains automated testing frameworks for enterprise applications. Develops automation scripts, validates APIs and web services, performs functional, regression, integration, and end-to-end testing, and applies BDD practices. Supports CI/CD integration, analyzes QA metrics, improves testing processes, and collaborates with engineering and business stakeholders to ensure software quality, reliability, performance, and maintainability.

Develop and maintain scalable full-stack applications, REST APIs, microservices, and responsive user interfaces. Integrate internal and third-party systems for real-time data synchronization, optimize application performance, implement security controls, and troubleshoot production issues. Collaborate with analysts, quality engineers, program managers, and data science teams to deliver enterprise applications. Support code reviews, CI/CD, deployments, monitoring, and ongoing maintenance.

Define and lead enterprise-wide AI/ML architecture strategy, standards, governance, reference architectures, and adoption roadmaps. Design scalable architectures for generative AI, LLM applications, RAG, AI agents, MLOps, data platforms, cloud infrastructure, security, and enterprise applications. Lead technology evaluations, architecture reviews, modernization strategies, responsible AI controls, vendor decisions, and transformation programs while advising executives and technical teams.

Leads large-scale, cross-functional programs from planning through delivery, defining scope, budgets, timelines, metrics, and governance. Manages interconnected projects, risks, resources, vendors, stakeholders, and executive communications. Drives change management, process improvement, issue resolution, and successful adoption of program outcomes while mentoring project managers. Requires 8–12+ years of project or program management experience, including enterprise-scale programs, and familiarity with Agile, Waterfall, or hybrid delivery methods.