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

Manages fraud risk platforms, models, rules, vendors, and system performance. Develops platform requirements and recommendations, coordinates risk services roadmaps with Product and Technology, tunes systems with Fraud Operations, evaluates vendor technologies, and reports on risk performance. Leads cross-functional risk strategy initiatives with autonomy while supporting the protection of systems, data, and financial transactions.

Designs, builds, and operates infrastructure-as-code capabilities using Terraform and Ansible across cloud and on-premises environments. Develops reusable modules, policy-as-code guardrails, testing frameworks, secure credential patterns, configuration automation, and developer self-service tooling. Partners with security, compliance, platform, network, and CI/CD teams to implement controlled infrastructure changes, automate evidence collection, manage drift, and improve reliability. The role also mentors engineers, documents architecture, and leads complex technical initiatives.

Hands-on principal engineer and technical leader responsible for software architecture, product design, engineering standards, and department-wide technical vision. Partners with product, architecture, engineering teams, and customers to shape solutions and technology roadmaps. Mentors engineers, leads cross-functional initiatives, presents to stakeholders, and supports risk management. The role requires extensive experience designing complex full-stack systems using Java, microservices, AWS, CI/CD, test automation, and related cloud and software development technologies.

Design, build, and operate a production AIOps agent platform for event observation, diagnosis, recommendations, and controlled automated actions. Develop agent runtimes, tool interfaces, event routing, telemetry, auditability, evaluation systems, feedback mechanisms, and operator experiences. Establish safety guardrails, approvals, permissions, rollback controls, and reliability standards. Collaborate across engineering, operations, security, risk, and compliance to deliver scalable, explainable, and regulated production capabilities.

Lead design, architecture, and delivery of scalable, distributed cloud-based systems. Own features end-to-end, guide technical planning, mentor engineers, improve engineering practices, resolve production issues, and collaborate with product and cross-functional teams.

The Senior ML Operations Engineer is responsible for building and maintaining ML infrastructure, model deployment processes, and collaboration with data teams to optimize predictive modeling solutions.

Drive vision, roadmap, and delivery of internal enterprise data platform capabilities. Define self-service workflows for data ingestion, curation, governance, metadata, observability, data quality, and access. Collaborate with engineering, analytics, architecture, governance, and security to translate user needs into scalable product requirements, measure adoption and performance, and ensure platform reliability, compliance, and developer productivity.

Design, build, and maintain scalable, reliable application infrastructure; automate deployments and recovery; implement observability and monitoring; troubleshoot performance bottlenecks; advise development teams on microservice best practices; produce runbooks; participate in 24x7 on-call rotation and ensure security and compliance.

The Technical Product Manager will develop analytical technology, define roadmaps, gather requirements, enforce quality standards, and support model deployment processes while collaborating with various teams.

The Distinguished Engineer drives cloud initiatives, leads large-scale systems design and implementation, and mentors teams while ensuring adherence to engineering best practices.