AI Product Manager

The Role You will be the only AI Product Manager at UKON, working closely with our Head of Engineering, CEO, and a small engineering team of approximately five people. You will have significant ownership over how product management operates and how we turn strategy into working software. This is not a traditional Product Manager role. You will spend time in the codebase, not just in roadmaps, meetings, and tickets. We are looking for a product leader who can move fluidly between customer problems, business strategy, system design, data, and code. You will use AI development tools, build functional prototypes, conduct technical spikes, and contribute production code. You should be comfortable opening pull requests, participating in code reviews, writing tests, debugging issues, and owning scoped technical projects through deployment. You are not replacing a software engineer, but coding will be a meaningful part of how you discover, validate, and deliver solutions. You will work alongside engineering to understand our architecture, data models, APIs, integrations, and technical constraints. Depending on the problem, your output might be a product strategy, technical specification, working prototype, SQL query, API integration, internal tool, analytics implementation, or production ready feature. You will not be handed a finished roadmap. Sales, marketing, wholesale, engineering, customers, and external partners all bring different priorities. Your job is to turn those inputs into clear product and technical decisions, determine what matters most, and keep the team focused on measurable outcomes. Cyber insurance remains highly manual and inconsistent. Terminology is not standardized, carrier workflows and APIs vary, critical data is often fragmented, and legal and geographic requirements affect how a product must work. Our agency and MSP channels also have needs that sometimes diverge and sometimes converge. You will turn that complexity into intelligent, scalable software. You will know when a problem requires durable infrastructure and when a lightweight experiment can help us learn faster. You should also be comfortable saying no when the evidence, technical reality, or product strategy calls for it. What You’ll Do Own the product process from discovery and prioritization through development, launch, measurement, and iteration. Partner directly with the Head of Engineering and CEO to shape the product strategy, technical roadmap, and build priorities. Design AI-native workflows that use context, automation, and intelligent assistance to help users complete meaningful work. Translate complex insurance and cybersecurity problems into clear requirements, data models, system behaviors, and acceptance criteria. Work directly in the codebase to build prototypes, complete technical spikes, fix issues, and ship scoped production features. Open pull requests, write tests, participate in code reviews, and own technical work through deployment. Evaluate where deterministic software is required and where AI can create a better, faster, or more adaptive experience. Help design AI systems that incorporate model selection, context engineering, retrieval, structured outputs, tool use, and human oversight. Establish evaluations and instrumentation to measure the quality, reliability, cost, and latency of AI-powered features. Work with third-party APIs, carrier integrations, data pipelines, and technical documentation to assess feasibility and identify constraints. Use AI development tools to accelerate research, coding, testing, prototyping, documentation, and analysis. Define success metrics and use product data, customer feedback, and business outcomes to evaluate what we ship. Gather input across the business and clearly communicate product decisions, technical tradeoffs, progress, and results. What You Bring At least five years of experience building and shipping software across product management, engineering, or a hybrid role, including meaningful ownership of product decisions. Demonstrated experience contributing production code within a collaborative software development environment. Proficiency in at least one modern programming language and the ability to become productive in an unfamiliar codebase. Experience with Git, pull requests, automated testing, code review, and modern deployment workflows. Strong technical fluency across APIs, integrations, databases, data modeling, analytics, and software architecture. Hands-on experience building AI-enabled products using language model APIs and related technologies. An understanding of context engineering, retrieval, structured outputs, tool calling, agentic workflows, evaluations, and human-in-the-loop systems. The judgment to balance model quality, reliability, speed, cost, privacy, security, and user experience. The ability to translate ambiguous user and business problems into both a long-term product vision and clear near-term technical requirements. Experience using tools such as Claude Code, Cursor, Codex, Devin, or similar platforms as part of your daily workflow. Strong communication skills and the ability to align technical and nontechnical stakeholders. Comfort operating in ambiguity, making difficult tradeoffs, and creating structure. A first-principles mindset and a strong bias toward building, shipping, learning, and iterating. Deep user empathy, strong product judgment, ownership, and a high bar for quality. Bonus Points Experience building agentic systems, retrieval pipelines, evaluation frameworks, or context-aware AI products. Experience in cybersecurity or familiarity with common cybersecurity frameworks, controls, and certifications. Experience in insurance, insurtech, fintech, or another regulated and high-trust industry. Familiarity with insurance agencies, agency management systems, cyber insurance carriers, or managed service providers. Experience building workflow-heavy B2B software or third-party integrations. Experience in a fast-moving, high-autonomy startup environment. What Success Looks Like UKON has a clear roadmap tied directly to customer needs and our most important outcome: protecting more businesses. You regularly contribute working code, prototypes, and technical solutions that help the team learn and ship faster. Engineers have the context, requirements, and product direction they need to move quickly and make strong decisions. AI is embedded meaningfully throughout the product instead of being treated as a standalone feature. AI-powered workflows are measurable, reliable, auditable, and designed with appropriate human oversight. Product decisions balance customer value, technical feasibility, speed, scalability, and business impact. New features are measured against clear success metrics and improved through real-world feedback. UKON turns more complex cyber insurance processes into intelligent, scalable workflows that help agencies and MSPs protect more businesses.