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

Build high-performance, real-time Angular UIs for AI-driven agent workflows. Implement SSE/WebSocket streaming, complex state management (Signals/NgRx), observability dashboards, HITL controls, performance optimizations, and collaborate on API/JSON schema design with backend and AI engineers.

Own product vision and roadmap for a cloud-native data platform on GCP. Translate business needs into epics and user stories, prioritize ETL/ELT, databases, streaming, and BI work, coordinate onshore/offshore teams, ensure data governance, quality, and analytics readiness, and drive adoption of Snowflake and DOMO-based analytics.

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.

Design, build, and maintain operational and analytical data platform capabilities using Java Spring Batch, Python, AWS, Oracle, and Snowflake. Deliver end-to-end development, production rollout, and support; improve financial product data quality, modeling, and SQL performance; collaborate with business partners and squads.

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.

Customer-facing Forward Deployed Engineer who architects, implements, and optimizes agentic AI proofs-of-concept and enterprise deployments. Leads solution design, agent orchestration, platform development, performance optimization, and cross‑functional delivery while mentoring distributed technical teams and ensuring production-ready MLOps, FinOps, and security/compliance practices.

Lead testing strategy and automation for enterprise web applications and APIs. Build and maintain Java-based Selenium/Serenity automation, design reusable test artifacts, participate in Agile ceremonies, log and track defects, verify production releases, and promote a quality-first mindset across teams.

Build and maintain scalable Python/FastAPI backend services, integrate generative AI and LLMs, implement RAG/vector DB semantic search, design agent-based workflows, develop APIs and microservices, enable async/event-driven processing, support cloud-native deployments (Docker/Kubernetes), and collaborate across frontend, DevOps, and product teams to deliver secure, observable AI-driven employee support platform.

Design, build, and scale production-ready generative AI systems: multi-agent workflows, advanced RAG pipelines, LLM integration and fine-tuning, scalable FastAPI backends, Dockerized deployments, monitoring, and GenAI optimization for latency, cost, and reliability.

Lead design and implementation of high-performance Apache Camel routes and microservices, apply enterprise integration patterns, migrate TIBCO processes to Camel, optimize Java/Camel performance to meet SLAs, implement secure MFT/encryption and protocol integrations (SFTP, AS2, JMS/Kafka, REST/SOAP), build containerized solutions (Docker/Kubernetes/OpenShift), enforce rigorous testing, and mentor the engineering team.