Director of Product

Lightyear is building the operating system for enterprise AI consumption: the layer that measures, governs and optimizes how organizations spend on tokens, models and agents. We are hiring a Director of Product, our founding product lead, to own what we build, in what order, and for whom.

The product is modular
- Lightyear's basic offering gives finance and engineering leaders attribution of AI spend by developer, model, team and project, empowering them to optimize usage and spend. Advanced tiers are deployed directly into an enterprise's operations, optimizing model routing and budget in real time.

This is a 0-to-1 role. You will define the MVP, recruit and run design partners, set the methodology for attributing token spend and connecting it to work outcomes, carry the technical half of the sale with Fin Ops leads, platform and AI engineering teams, finance, and the CTOs and heads of AI who must justify the AI budget, and build the product function from scratch.

You should be as comfortable debating gateway architecture and telemetry schemas with engineers as you are sitting across from a CFO explaining the return on their AI spend. You will be the founding product lead and first product hire, with a mandate to hire and lead the product and design team as Lightyear grows.

• Own the product roadmap and the definition of product-market fit, from MVP through the Pro-to-Enterprise ladder, and decide the build sequence across the module set: spend visibility and attribution, token credit request and approval, usage governance and compliance, model optimization, routing and procurement, outcome and productivity measurement, and data and indices
• Define Lightyear Pro: agents and SDKs export their own telemetry, metadata only (no access to underlying prompts or code), minimal admin credentials, customers keep their existing LLM-provider subscriptions, with usage and cost tracked by developer, model, team and project
• Define Lightyear Enterprise with engineering: gateway and console running single-tenant in the customer's cloud, model and budget rules enforced in the request path, and routing of each task to the model with the highest measured return on cost
• Own the outcome and productivity measurement pillar: join token spend to the work it produced (pull requests merged, tickets resolved, features shipped, support cases closed) through integrations with Git Hub, Jira, Linear and similar systems, so customers can see marginal productivity per project, per team and per dollar, not only cost
• Own the measurement methodology: how token spend is attributed across providers and plan types (individual, team, API, enterprise), normalized, and connected to the work it produces, so that "spend productivity" is a number Fin Ops, finance, engineering leaders and auditors trust; measure efficiency (cost per unit of output) rigorously rather than claim revenue attribution
• Own the token expense-management workflow (request, approval, suggested allocation) as the differentiating hook of the Pro product, with the same ambition that Concur brought to T&E and Deel to payroll
• Define how the data and index layer (inference token benchmarks and indices) is produced from product telemetry, and the product logic for what is published free, licensed, and reserved for Hivemind Capital's financial products
• Treat privacy and security posture as product requirements: metadata-only ingestion, data residency, single-tenant deployment, and the path to enterprise compliance (SOC 2, policy enforcement for corporate and regulatory AI usage rules)

• Recruit and run the design-partner program: five to ten organizations already running agents at scale, converting…