Product Manager

Cleo is a dynamic company focused on building intelligent products that customers love. They are seeking an experienced AI Product Manager to lead the development of AI-powered products, collaborating with cross-functional teams to define and execute the product roadmap.

Responsibilities:

• Own the AI product roadmap — including LLM-powered features, predictive models, agentic workflows, and ML-driven automation — translating customer needs into a prioritized, outcome-driven plan
• Develop a deep understanding of customer experience, identify product gaps where AI can deliver disproportionate value, and generate new ideas that grow market share, improve customer experience, and drive growth
• Partner closely with data scientists, ML engineers, and software engineers to scope models, evaluate tradeoffs between accuracy, latency, cost, and UX, and ship with quick time-to-market and optimal resources
• Translate product strategy into detailed requirements and prototypes, including user stories, MVP scope, acceptance criteria, model evaluation criteria, and KPI frameworks tied to measurable customer outcomes
• Define and monitor AI feature success metrics — including model performance (precision, recall, accuracy), user adoption, and business impact — through dashboards and regular reporting to executive leadership
• Conduct structured buy / build / partner analysis for new AI capabilities, including evaluation of foundation model providers, third-party AI vendors, and open-source alternatives
• Scope and prioritize activities based on business and customer impact, balancing near-term wins with longer-horizon AI investments
• Drive product launches in collaboration with marketing, PR, executives, and other PM team members — including positioning AI capabilities clearly and avoiding overpromising
• Evaluate promotional plans to ensure messaging accurately conveys AI capabilities and limitations, and is consistent with the broader product line strategy
• Act as an AI product evangelist — both internally and externally — to build awareness, understanding, and trust in our AI capabilities
• Represent the company by visiting customers to solicit feedback on AI features, observe real-world use, and surface opportunities for the next wave of intelligent product capabilities

Requirements:

• BS/MS degree in Computer Science, Engineering, Data Science, or equivalent practical experience
• 3–5 years of proven product management experience, with at least 1–2 years owning AI/ML-powered product features in a SaaS environment
• Proven track record of managing all aspects of a successful product throughout its lifecycle — from discovery through launch and iteration
• Demonstrated ability to develop product and AI strategies and effectively communicate recommendations to executive leadership
• Solid technical background with hands-on understanding of software development, modern AI/ML technologies (LLMs, embeddings, classical ML), and SaaS architectures
• Ability to read and interpret ML model outputs, understand evaluation metrics (precision/recall, AUROC, RMSE, F1, eval sets for LLMs), and hold technical teams accountable to model quality
• Strong written, verbal, presentation, and communication skills — especially the ability to explain AI concepts to non-technical audiences
• A passion for usability, user empathy, and a knack for simplicity — particularly in designing AI experiences that build user trust
• Strong problem-solving skills and willingness to roll up your sleeves to get the job done
• Skilled at working effectively with cross-functional teams in a matrix organization
• Hands-on experience shipping LLM-based product features, RAG architectures, fine-tuned models, or agentic AI applications
• Familiarity with AI governance frameworks, model explainability, evaluation harnesses, and responsible AI practices
• Experience defining prompt engineering standards, eval pipelines, or human-in-the-loop workflows for AI products
• Exposure to MLOps tooling and lifecycle (model training, deployment, monitoring, drift detection)