Senior Commercial Broker, Brokerage Intelligence
- Market p25–p75
- $135k–$198k
- Harper Group p25–p75
- $130k–$170kn=29
- Opened · 30d
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- Closed · 30d
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- Opened · 7d
- +1,5896% of open
- All other
- 624,472open
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. Your job is to make that judgment teachable, testable, and reusable across Harper.
This role does not sell or originate insurance, own a book, carry a sales quota, close customers, or make final account-level placement decisions.
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. New York and San Francisco are the on-site homes for this senior brokerage and product work.
Why now
Harper serves many industries, coverage lines, and market paths. The company already generates enormous amounts of brokerage judgment through real accounts, market responses, exceptions, and outcomes. The opportunity is to turn that judgment into infrastructure instead of letting it disappear inside individual conversations.
The Senior Commercial Broker sits where commercial insurance practice meets product and strategy. You study how brokerage work is actually done, decide what excellent judgment looks like, encode it into workflows and decision standards, train AI systems and people against those standards, and use what fails in practice to improve Harper's products and operating model.
The mission is larger than documenting today's process. You will help define what the brokerage process should become when expert people and capable AI systems work together.
How you work with the team
You partner closely with product and engineering to turn brokerage judgment into useful tools and reliable AI evaluations. You bring the insurance standard and the evidence. Product leaders make roadmap and release decisions.
You also work with placement teams, licensed brokers, underwriters, and account owners who execute individual accounts. You define and evaluate how strong market selection, submission, negotiation, recommendation, and binding should work. They keep the final decision on each account.
You create the brokerage content, cases, and decision standards. Harper's learning and enablement teams help deliver them across the company.
What you own
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.