AI Product Manager

UKON•Denver, CO

21d•$180,000 - $220,000

About The Position

The AI Product Manager at UKON will be the sole individual in this role, collaborating closely with the Head of Engineering, CEO, and a small engineering team of approximately five people. This position offers significant ownership in shaping product management operations and translating strategy into functional software. Unlike a traditional Product Manager role, this position involves hands-on work within the codebase, going beyond roadmaps, meetings, and tickets. The ideal candidate is a product leader capable of navigating customer problems, business strategy, system design, data, and code. Responsibilities include utilizing AI development tools, building prototypes, conducting technical spikes, and contributing production code. This involves opening pull requests, participating in code reviews, writing tests, debugging, and managing scoped technical projects through deployment. While not a replacement for a software engineer, coding will be integral to discovering, validating, and delivering solutions. The role requires understanding the existing architecture, data models, APIs, integrations, and technical constraints. Outputs can range from product strategy and technical specifications to prototypes, SQL queries, API integrations, internal tools, analytics implementations, or production-ready features. The Product Manager will be responsible for synthesizing diverse inputs from sales, marketing, wholesale, engineering, customers, and partners into clear product and technical decisions, prioritizing effectively, and focusing the team on measurable outcomes. The cyber insurance industry is characterized by manual processes, inconsistent terminology, varying carrier workflows and APIs, fragmented data, and complex legal/geographic requirements, with distinct needs from agency and MSP channels. The AI Product Manager will transform this complexity into intelligent, scalable software, discerning when durable infrastructure is needed versus when lightweight experiments are appropriate, and confidently saying 'no' when necessary based on evidence, technical reality, or product strategy.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.