AI Product Lead: From Discovery to Live AI Solutions

Brillio; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Brillio is seeking a product leader to translate ambiguous enterprise AI problems into buildable, value-driving solutions. You will own discovery, roadmap, adoption and measurable value across AI-native products.

Responsibilities include leading customer discovery, defining PRDs and MVP scope, shaping AI-assisted workflows, collaborating with engineers and architects, running prototypes and validating with users. You will craft metrics and post-launch learning loops to prove impact.

Qualifications

• 5-8 years total experience across product management, product engineering or adjacent technical product roles.
• At least one product or major feature taken from discovery through launch.
• Working knowledge of LLM applications, RAG, agents, APIs and evaluation.
• Ability to create a prototype, structured workflow or technically credible product demo.
• Strong written product thinking and stakeholder communication.

Responsibilities

• Lead customer and stakeholder discovery; map workflows, users, friction and desired outcomes.
• Define product vision, PRDs, MVP scope, backlog and acceptance criteria.
• Design AI-assisted and agentic workflows with appropriate human control points.
• Partner with the Technical Architect on feasibility, platform choices and build-versus-buy decisions.
• Run prototypes, user validation and live product demonstrations.
• Define product metrics, adoption signals, cost/value assumptions and post-launch learning loops.

Skills

Product discovery & problem framing

Zero-to-one delivery

AI product literacy

Prioritization & value

Technical prototyping

Communication & leadership

Job description

Brillio is seeking a product leader to translate ambiguous enterprise AI problems into buildable, value-driving solutions. You will own discovery, roadmap, adoption and measurable value across AI-native products.

Responsibilities include leading customer discovery, defining PRDs and MVP scope, shaping AI-assisted workflows, collaborating with engineers and architects, running prototypes and validating with users. You will craft metrics and post-launch learning loops to prove impact.