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

Own nationwide insurance rate and form filings across all 50 states, including preparing filing packages, coordinating with carrier partners and actuaries, responding to regulator objections, tracking approvals, and implementing approved forms in the underwriting platform. Draft and revise policy forms and endorsements, maintain filing libraries, ensure issued policies match filed content, and resolve underwriting and policy issuance questions across teams.

Leads Shepherd’s financial planning, accounting, controls, reporting, treasury, and risk-bearing capital infrastructure. Owns operating plans, forecasts, contribution-margin analysis, board and investor reporting, audits, tax, fiduciary accounts, carrier payments, and bordereaux reconciliation. Oversees Finance, Revenue Operations, Business Operations, and Analytics teams while partnering with executives, carriers, reinsurers, investors, and engineering. Builds scalable finance systems, manages outsourced accounting, and supports fundraising and organizational growth.

Own Shepherd’s marketing strategy for commercial insurance brokers, including field marketing, events, content, digital campaigns, and brand development. Build repeatable event programs, create broker-focused content, measure engagement and submissions, manage budgets and agencies, and hire and develop the marketing team. Partner closely with underwriting, business development, leadership, revenue operations, and analytics to drive broker relationships and business growth.

Lead the launch and growth of Shepherd’s wholesale E&S insurance business and brand. Define products, underwriting appetite, broker distribution strategy, capacity partnerships, and financial targets. Hire and manage underwriting and distribution teams, establish authority and audit frameworks, collaborate on technology-enabled workflows, and own premium, profit, loss-ratio, retention, and expense results. Build broker and reinsurer relationships while coordinating with claims, actuarial, finance, product, engineering, and data teams.

Build and own Shepherd’s canonical analytical layer using dimensional modeling and dbt. Partner with actuarial, reporting, operations, engineering, and other data consumers to define trusted business entities, facts, dimensions, relationships, and rules. Establish testing, reconciliation, documentation, lineage, and adoption practices; evaluate and migrate existing models and datasets; and shape semantic context for human and AI-assisted analytics.

Lead Inland Marine technical underwriting, including referral decisions, account reviews, guidelines, authority governance, audits, coverage forms, training, and capacity partner support. Partner with Claims, Actuarial, Data, Product, Engineering, and Compliance to improve underwriting practices, embed requirements into platform workflows, and manage complex Builders Risk and commercial construction risks.

Analyze commercial P&C insurance rates, filings, competitors, loss ratios, portfolios, and regulatory requirements. Build rating plans, support rate and form filings, respond to regulatory objections, and monitor product performance. Use SQL and PostgreSQL for data analysis, Metabase for dashboards, and dbt for data transformation. Collaborate with actuarial, underwriting, compliance, product, and engineering teams to translate insights into pricing and product decisions.

Manage broker-partner relationships and post-sales account processes, lead customer demos, onboarding, meetings, and business reviews, and expand software adoption. The role also improves customer journeys, documents processes, supports internal training, and collaborates cross-functionally on process development and customer experience initiatives.

Design, build, and deploy LLM-powered features and production AI infrastructure (model serving, inference, evaluation, monitoring) that improve underwriting, pricing, and internal tooling. Partner with product, engineering, underwriting, and data teams to deliver end-to-end AI solutions and establish prompt engineering and evaluation best practices.

As a Machine Learning Engineer, you will build end-to-end ML systems for autonomous underwriting, collaborating with underwriters and engineers to advance ML capability.