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

The Business Engagement Lead - Finance Operations ensures alignment between Finance and Technology, overseeing business requirements, product roadmaps, and stakeholder engagement while monitoring outcomes and driving technology investments to match business goals.

The Exposure Data Manager leads analytics to understand exposure patterns, enforces data standards, ensures data quality, and collaborates across departments for effective exposure management.

Lead reliability and observability for the financial data platform: define SLOs/SLIs, build metrics pipelines, extend instrumentation across Velocity, Redpanda, MuleSoft, Snowflake, Fabric, and AWS; implement incident management (Datadog -> Incident.io -> ServiceNow), scale automation and remediation, and design AI-assisted SRE agents using Cursor for triage and root-cause analysis.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

Manage onboarding, policy administration, and bordereaux workflows; ensure data integrity and SLA adherence; produce reports using Snowflake, Power BI, and Excel; collaborate cross-functionally to document SOPs and implement process improvements.

Design, build, and operate scalable web applications, APIs, services, and AI-enabled workflows. Use AI tools across the development lifecycle, ensure reliability, performance, and observability, contribute to technical decisions, iterate from user feedback, and own production quality and delivery as part of cross-functional squads.

Lead discovery, roadmap, and delivery of data platform capabilities for the Accelerant Risk Exchange. Define strategy, prioritize ingestion/consumption features, collaborate with stakeholders and engineering, champion AI-native experimentation, and communicate outcomes to internal and external partners.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Design, implement, and operate secure, scalable multi-cloud infrastructure (Azure/AWS) with IaC (Terraform), managed Kubernetes, containers, and AI platform support. Lead complex projects, define operational processes, ensure security/compliance, mentor teammates, and maintain observability for production systems.