Tech Product Manager, Fractal

• Experience leading AI/GenAI initiatives from use-case discovery and PoC through production deployment (where applicable)
• Strong stakeholder management and requirements elicitation skills, including prioritization of scope for PoC delivery
• Hands-on proficiency with AI tools for mockups, meeting-note synthesis, workflow acceleration, and rapid artifact creation
• Strong understanding of LLM-based systems, prompt design, and RAG architectures
• Experience defining and implementing AI evaluation frameworks, including prompt benchmarking, regression testing, A/B testing, and human-in-the-loop evaluation
• Familiarity with GenAI observability/evaluation tooling (e.g., LangSmith, LangFuse, MLflow, Weights & Biases, Azure AI Studio, OpenAI Evals)
• Experience tracking model/application metrics (e.g., accuracy, hallucination rate, latency, cost per request, drift) and translating them into business outcomes and ROI
• Demonstrated executive communication skills with the ability to present technical and financial insights to senior leadership

Desirable

• We are seeking a GenAI Technical Product Manager to lead the intake, evaluation, and delivery of Generative AI solutions across the enterprise
• This role will partner closely with business stakeholders to understand requirements, prioritize scope for proof-of-concept (PoC) initiatives, and mitigate delivery and adoption risk while showcasing the art of the possible
• The ideal candidate combines strong product leadership with hands-on use of AI tools, practical understanding of GenAI systems and evaluation frameworks, and the ability to translate AI performance into measurable business value ($ impact)
• Lead intake of business ideas and translate stakeholder needs into clear GenAI use cases and product requirements
• Facilitate stakeholder conversations to define and prioritize PoC scope based on business value, feasibility, and risk
• Use AI tools hands-on to accelerate discovery and delivery (e.g., create mockups/prototypes, synthesize meeting notes, extract requirements, draft artifacts)
• Drive PoC execution and decision-making, balancing technical performance with business outcomes and risk mitigation
• Define and run evaluation strategies (quality, reliability, safety, latency, cost), and connect AI metrics to business KPIs and financial impact
• Partner with business PMs to quantify benefits after PoC completion, including productivity gains, cost reduction, risk reduction, and revenue impact
• Communicate recommendations, trade-offs, and quantified value to senior/executive stakeholders

• End Date: April 24, 2026