Product Engineer

Accountabilities

• Own product features end to end, from defining scope and identifying dependencies through development, deployment, customer adoption, and iteration.

• Work across the full technology stack as needed, including user interfaces, APIs, data models, backend services, background jobs, and infrastructure integrations.

• Transform complex, data-heavy insurance information into clear, intuitive interfaces that professionals can rely on in their daily workflows.

• Lead a product squad and take responsibility for a defined area of the platform, with ownership aligned to your strongest technical and product instincts.

• Identify dependencies on adjacent teams or systems, clearly define what is required, and proactively address potential blockers.

• Use AI coding tools, agents, and agentic workflows extensively to accelerate development and increase engineering leverage.

• Contribute to model evaluation and benchmarking initiatives, helping determine which AI models and approaches are appropriate for customer-facing and data-sensitive workflows.

• Develop and improve internal evaluation harnesses where they can outperform or provide greater reliability than direct model calls.

• Apply strong product judgment to challenge unclear requirements, simplify solutions, prioritize high-value work, and discontinue features that do not deliver sufficient value.

• Work closely with Product Designers and Infrastructure/Platform specialists to turn ambiguous problems into effective, production-ready experiences.

• Continuously identify opportunities to improve the product, engineering workflows, and underlying data systems.

• Take ownership of outcomes rather than waiting for detailed specifications, established processes, or predefined implementation plans.

Requirements:

• At least 2 years of experience building and shipping production web applications; candidates with significantly more experience are equally welcome, with demonstrated ability to take problems through to completion being the key consideration.

• Advanced, hands-on daily experience using modern AI development tools such as Codex, Claude Code, or comparable agentic coding workflows.

• Strong full-stack engineering capabilities and comfort moving between frontend, backend, data, and supporting systems.

• Experience working with data-heavy products such as dashboards, analytics platforms, pricing systems, operational tools, or other applications involving complex datasets.

• Strong product instincts and a clear bias toward shipping useful solutions rather than optimizing for process.

• Ability to independently understand ambiguous problems, make sound technical and product decisions, and drive work through to production.

• High autonomy and self-direction, with the ability to make meaningful progress without extensive processes or management layers.

• Strong communication and collaboration skills within a small, senior, highly empowered team.

• Willingness to take ownership of both technical implementation and product outcomes.

Nice to have:

• Experience in insurance, financial services, or another regulated and data-intensive industry.

• Exposure to real-time data products, market indexes, benchmarks, pricing platforms, or similar systems.

• Experience working at an early-stage company where you have taken on multiple responsibilities across product and engineering.

• Interest in financial markets, market structure, pricing transparency, or data infrastructure.

• Experience working with AI evaluation, benchmarking, model selection, or production AI systems.

• Experience building products where data quality, reliability, and customer trust are critical.

Benefits:

• Competitive salary range of$115,000–$190,000 USD.

• Equity or stock options in addition to base salary.

• Standard health and wellness benefits.

• Work-from-home stipend.

• Learning and development budget.

• Team events and opportunities for collaboration.

• Mentorship and exposure to experienced industry leaders from organizations across finance, technology, and product.

• High degree of autonomy and ownership within a small, senior team.

• Hybrid and remote working options.

• Opportunity to work on complex, high-impact problems at the intersection of software, AI, data, and financial infrastructure.