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

Own end-to-end analytics pipelines for AI usage, developer experience, engineering productivity, and spend. Instrument telemetry, build governed ETL workflows, define trusted metrics, and create executive dashboards and visual narratives. Analyze results, recommend improvements to AI ROI and developer experience, and communicate methodology to senior stakeholders. Collaborate across data engineering, applied AI, and data science while using AI coding agents to build, test, and maintain production data systems.

Staff Software Engineer responsible for building and operating Block’s card issuing platform at the network boundary. The role requires deep expertise in card networks, ISO 8583, authorization and clearing flows, certifications, mandates, and direct network connectivity. Responsibilities include writing production code, developing conformance tooling, debugging protocols, leading cross-team technical initiatives, influencing network requirements, mentoring engineers, supporting AI-assisted development, and participating in on-call operations for critical financial systems.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, lifecycle intelligence, and next-best-action decisioning. Design reliable signal contracts with freshness, provenance, confidence, and calibration guarantees. Lead experimentation, monitoring, feedback loops, and impact evaluation focused on fairness, trust, risk, compliance, and long-term engagement. Partner across product, growth, data, platform, modeling, risk, and compliance teams.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Own complex Banking design initiatives end to end, creating zero-to-one financial product experiences and improving existing products. Set the design quality bar, shape product vision and strategy, prototype with AI and emerging tools, and translate financial and regulatory complexity into clear experiences. Partner with Product, Engineering, Risk, Compliance, and Research while extending design systems and mentoring designers through critique, feedback, and hands-on example.

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Build and own foundational Android platform infrastructure, shared libraries, frameworks, architecture, observability, performance tooling, and developer experience systems. Lead AI-native engineering practices, evaluate AI development tools, drive cross-organizational technical initiatives, mentor engineers, and establish scalable Android standards. Collaborate across mobile, web, backend, product, design, and leadership teams to improve engineering velocity and customer experiences.

As a Staff Software Engineer, you will lead technical strategies, drive architectural decisions, mentor engineers, and develop consumer banking solutions using various technologies.

Lead end-to-end data science for lending products: define measurement frameworks, analyze experiments and cohorts, evaluate risk and model performance, use AI tools to accelerate analysis, build reusable tooling, and mentor junior scientists while partnering with product, engineering, and risk stakeholders.