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

Lead quality efforts for a web platform and APIs by designing/executing manual and automated tests, building test suites (UI, API, integration), integrating tests into CI/CD, investigating failures, and driving cross-functional quality improvements.

Design and build simulation environments modeling CTV auction mechanics, bidding strategies, and campaign outcomes. Create counterfactual frameworks, AI agents for experimentation, and use simulation to validate ML deployments. Define technical direction and mentor engineers.

Manage a portfolio of client accounts for a CTV advertising platform: launch and optimize campaigns, develop strategic account plans, drive revenue through upsell/cross-sell, analyze performance metrics, collaborate with internal teams, mentor junior staff, and use AI tools to accelerate optimizations and reporting.

Lead strategic relationships for gaming clients, launch and optimize programmatic CTV campaigns to meet CPA/CPI/ROAS targets, develop account plans and QBRs, drive upsell and retention, analyze funnels and metrics, collaborate with sales/product/AdOps, mentor junior staff, and use AI to accelerate campaign optimization.

Lead product vision and execution for CTV creative tooling: asset ingestion, generation, variant production, and creative-aware optimization. Build AI-driven tools to convert brand assets into TV-ready commercials, integrate creative signals into prediction/optimization models, partner with commercial teams for adoption, and represent the company externally.

Lead design and implementation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and services to ingest, normalize, link, and version identity data. Ensure auditable matching, data lineage, quality checks, schema enforcement, access controls, and privacy-by-design. Collaborate cross-functionally with product, analytics, legal, privacy, and security teams and create documentation, monitoring, and runbooks.

Design and operate ML training and serving infrastructure, build a Kubernetes+Ray backend, improve developer experience and observability, mentor engineers, and ensure reliable, secure deployments for low-latency, high-performance systems.

Act as the technical lead during sales: scope integrations, recommend measurement/attribution solutions, troubleshoot implementation issues, translate technical concepts for clients, and liaise with Product/Engineering/Customer Success. Document best practices and use AI tools to accelerate discovery, troubleshooting, and documentation to ensure successful onboarding and long-term client outcomes.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

Design, build, and scale backend contract and billing services supporting CPA and CPM models. Implement contract lifecycle, rate management, APIs, and integrations with finance. Ensure data integrity, auditability, reliability, observability, and performance. Lead technical design, mentor engineers, and collaborate with Product, Finance, and Data teams.