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

Lead systems analyst within an agile data squad to gather requirements, perform data analysis and mapping, modernize data platforms, validate data using SQL/Python, support ETL initiatives, and produce technical specifications and documentation for database projects.

Lead architecture, design, and delivery of Generative AI and ML solutions. Build scalable ML pipelines, LLM and RAG-based applications, vector DB integrations, and agent workflows. Drive MLOps, CI/CD, observability, security, and enterprise model orchestration. Provide technical leadership, mentor engineers, run Agile development, and shape AI strategy through POCs and platform innovation.

Design, build, and deploy production-ready generative AI applications: architect multi-agent workflows, implement advanced RAG with vector DBs, integrate/swap LLMs, fine-tune models, and deliver scalable FastAPI-based services with monitoring, CI/CD, and containerized deployment.

Design and document consistent software architecture across the engineering organization, guide architecture decisions, support developers on design issues, implement and improve core infrastructure and SDLC, develop technical/business approaches and tools, resolve technical roadblocks, and perform performance characterization and trade-off studies.

Lead migration from AEM 6.5 to AEMaaCS: assess implementations, architect cloud-native components, manage content migration with CTT, redesign dispatcher, implement CI/CD via Adobe Cloud Manager, modernize integrations, train teams, and provide post-migration support and technical documentation.

Lead UX strategy and execution for complex, data‑heavy enterprise finance applications focused on risk, compliance, audit, and governance. Translate regulatory requirements into information architecture, user journeys, dashboards, and prototypes. Design scalable interaction models and simplify rule‑heavy workflows while collaborating with product, engineering, and compliance teams.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.

Design and deliver high-fidelity interfaces and interactive prototypes for transactional retail workflows (search, quoting, inventory, payments). Adapt designs for varied retail hardware, contribute to a centralized design system, collaborate with developers to ensure feasibility within routing-layer architecture, and iterate based on discovery and pilot feedback to reduce friction in payment and quoting tasks.

Build, optimize, and scale production Generative AI applications. Design multi-agent systems and LangGraph workflows, implement advanced RAG with LlamaIndex and vector DBs, fine-tune and deploy LLMs, and create high-performance FastAPI async backends. Improve latency, cost, and reliability, containerize services with Docker, and manage monitoring, API security, and CI/CD for ML deployments.

Design and implement data federation and lakehouse architectures, build scalable ETL/ELT pipelines with Python and Spark, optimize performance across federated queries, manage Delta/Iceberg/Hudi tables, and enforce governance, security, and access controls for analytics and AI teams.