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

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.

Lead vision, strategy, and roadmap for Adobe-based MarTech solutions. Manage backlog, collaborate with marketing, analytics, UX, and engineering, drive AEM/Analytics/Target/Campaign/Journey implementations, define KPIs, run Agile ceremonies, and ensure data privacy and governance.

Lead modernization of the Salesforce ecosystem by optimizing development practices, reducing technical debt, improving performance and integrations, implementing best practices and governance (focus on Service Cloud), driving version control adoption, and providing technical leadership and training to create scalable, cost-effective solutions.

Translate ambiguous business problems into AI-native product opportunities. Develop future-state, prompt-driven experiences, hyper-personalized journeys, and strategic narratives. Lead cross-functional teams, benchmark AI product trends, and present executive-ready transformation roadmaps.

Lead a team delivering end-to-end Salesforce integration solutions: plan sprints, design and build APIs/middleware (MuleSoft/Boomi/Informatica), enforce coding standards, modernize integration landscape, troubleshoot issues, mentor developers, and coordinate testing/deployment and documentation.

Owns product management activities and roadmap for assigned products. Conducts technical and market research, defines product requirements with engineering and UI, coordinates cross-functional teams, builds business cases and vendor relationships, manages ROI and financial forecasting, measures impact of features, and identifies opportunities for innovation and growth.

Design, build, deploy, and maintain enterprise integrations and automations using Workato. Integrate SaaS, cloud, and on‑prem systems via APIs, webhooks, and event architectures; implement data mapping, transformations, security (OAuth2, JWT, SAML/SSO); monitor, troubleshoot, and optimize production integrations; establish logging/alerting and support processes; collaborate with stakeholders and mentor junior engineers.

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.

Design, implement, and manage large-scale GCP infrastructure using IaC (Terraform), containerization (Kubernetes/Docker), monitoring, security, and DR. Mentor junior engineers, optimize performance and costs, and document practices.