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Lucanet is seeking a Senior AI Product Manager to drive the vision and execution of the Intelligence Core and Lume, the company's shared AI capability platform. This role sits at the intersection of product strategy, AI innovation, and cross-functional coordination in a fast-moving fintech environment where accuracy and trust are non-negotiable for finance teams.
You will own the complete product lifecycle for the Intelligence Core and Lume—from discovery and roadmap prioritization through launch and post-launch analytics. Key responsibilities include:
• Owning the product vision, roadmap, and lifecycle for the Intelligence Core and Lume shared AI capability
• Prioritizing AI features using data-driven frameworks, tying each to measurable business outcomes, and tracking adoption post-launch
• Defining and owning the AI evaluation strategy, both offline (curated datasets and benchmarks) and online (live production quality signals)
• Maturing LLMOps best practices across the agent and product lifecycle and centralizing AI product reporting
• Running customer discovery and early-access programs with working prototypes to validate solutions before committing to a path
• Coordinating AI initiatives across R&D and aligning Product, Engineering, Delivery, and go-to-market teams through influence rather than formal authority
• Tracking the AI frontier—new model releases, research, tooling, and competitor launches—and translating insights into concrete product opportunities
• Contributing to AI pricing and packaging strategy and enabling Sales, Marketing, Support, and Customer Success with value-proposition briefs
You will report into the Product AI leadership team and work within a small, highly talented AI product team that values pragmatic collaboration, comfort with ambiguity, and continuous learning at the edge of AI innovation.
REQUIREMENTS:
• Owned the roadmap and lifecycle of an enterprise software product, from discovery to launch, using customer discovery and product analytics to reach measurable business outcomes
• Working knowledge of modern AI/ML including LLMs, RAG, agents, agentic harness, prompt and context engineering, and understanding of fine-tuning vs. prompting trade-offs, with depth in at least one area such as Agent UX, LLMOps, or AI evaluation
• Ability to track the AI frontier (new model releases, research, tooling, techniques) and quickly judge what matters for finance use cases
• Daily hands-on use of LLMs and AI tools such as Claude, ChatGPT, Claude Code, Cursor, or Codex to prototype ideas and turn concepts into working demos in hours
• Pragmatic, collaborative, low-ego mindset: comfortable with ambiguity, able to lead through influence without formal authority, and committed to continuous learning in a fast-moving AI environment
