
Harper
Senior Commercial Broker, Brokerage Intelligence
San Francisco · Senior
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About the role
- SENIOR COMMERCIAL BROKER, BROKERAGE INTELLIGENCE Role in one line: Turn expert commercial brokerage judgment into the systems, training, and product recommendations that define how Harper brokers insurance.
- The hardest brokerage decisions rarely begin as clean rules.
- They live in the judgment of people who have seen a difficult risk, a thin submission, an unusual coverage structure, and a market exception before.
Responsibilities
- You will work deeply with product, engineering, operations, and insurance teams to build the brokerage infrastructure behind the work: the workflows people follow, the standards AI systems are evaluated against, the training that changes behavior, and the feedback loops that make the whole operation improve.
- Harper is building an AI-native brokerage, and that only works if expert judgment becomes something people and systems can learn from.
Compensation
- You understand general liability, property, workers' compensation, commercial auto, umbrella, and specialty coverage well enough to recognize the material facts, tradeoffs, and exception paths.
Benefits
- Harper offers health, dental, and vision insurance.
- Harper serves many industries, coverage lines, and market paths.
- Office-specific benefits are set by working location.
Company info
- Encode brokerage judgment. Turn complex commercial decisions into clear workflows, decision standards, playbooks, examples, and escalation rules without flattening away the judgment that matters.
- Define brokerage product requirements. Work with product and engineering to identify the brokerage problems worth solving, define what the product must understand, and recommend capabilities grounded in expert evidence.
- Train and evaluate AI systems. Build realistic cases, expected outcomes, grading standards, and failure examples. Review AI behavior against source evidence and expert judgment, then turn failures into permanent evaluations and product improvements.
- Design and evaluate brokerage workflows. Encode how information, decisions, exceptions, and handoffs should move through account processes. Test whether the workflow produces sound judgment without taking over its individual accounts.
- Own the brokerage learning standard. Create the content, cases, worked examples, decision standards, and effectiveness measures that make expert brokerage judgment teachable. Collaborate with the learning and enablement owners on delivery.
- Run the expert feedback loop. Stay close to frontline work, difficult cases, market responses, and user behavior. Separate one-off exceptions from recurring patterns and route each to the right product, process, or training change.
- Set evidence standards. Make sure recommendations and decisions remain traceable to the real application, document, communication, quote, or market response that supports them.
- Raise the quality bar. Identify where a workflow produces inconsistent judgment, where an AI system sounds right but is wrong, and where a person cannot tell what to do next. Redesign the system until the standard is clear and usable.
- Priority brokerage workflows become clear enough to use, audit, and improve without flattening away expert judgment.
- AI evaluations distinguish grounded commercial reasoning from an answer that merely sounds convincing.
- Material failures become durable evaluation cases, product corrections, workflow changes, or explicit accepted limits.
- Training built from live cases changes how people and systems handle the work.
- Frontline evidence reaches product and engineering as a specific problem with a testable success condition.
- You have substantial commercial brokerage, wholesale brokerage, or placement experience across complex small and middle-market accounts.
This listing is sourced directly from Harper's careers page and normalized into a canonical job model.