AI Product Manager

Description/Responsibilities

We're building an AI Center of Excellence from the ground up, and we need a strategic, hands-on AI Product Manager to lead this initiative. This isn't about managing a team—it's about building the foundation, establishing best practices, and proving the transformative value of AI across Tivity Health.

You'll be the first dedicated AI Product Manager, working directly with executive leadership, data science, engineering, and business stakeholders to identify high-impact AI use cases, ship production AI products, and create the playbook for how we leverage AI to enhance member experiences and drive business outcomes.

This role is perfect for someone who thinks like a strategist, builds like a founder, and executes like an operator - someone who can move fast, navigate ambiguity, and turn AI potential into tangible results.

What You’ll Do

Stand Up the AI Center of Excellence (0-6 Months)

• Define the vision and strategy for AI at Tivity Health—what problems we solve, how we prioritize, how we measure success
• Establish governance frameworks for responsible AI development (ethics, privacy, bias mitigation, compliance with healthcare regulations)
• Create the AI product playbook —templated processes for ideation, experimentation, evaluation, and deployment
• Build cross-functional relationships with data science, engineering, legal, compliance, and business leaders to align on AI priorities
• Identify and prioritize initial AI use cases across member engagement, care coordination, operational efficiency, and business intelligence
• Establish measurement frameworks —define KPIs, OKRs, and success metrics for AI initiatives; build dashboards and reporting cadences

Ship AI Products (Ongoing)

• Own the end-to-end product lifecycle for AI initiatives—from discovery and requirements through design, build, launch, and iteration
• Partner with data science and engineering to translate business problems into technical solutions (predictive models, generative AI, automation, personalization)
• Define success metrics and KPIs for each AI product—track adoption, impact, ROI, and member/business outcomes
• Run experiments and pilots —test hypotheses, learn fast, kill what doesn't work, scale what does
• Ship production-ready AI features that directly improve member experiences (e.g., personalized recommendations, intelligent search, proactive outreach, chatbots)

Track, Measure, and Report Progress (Ongoing)

• Own progress reporting for all AI initiatives—communicate status, blockers, wins, and risks to executive leadership and stakeholders
• Monitor and analyze performance against OKRs, KPIs, and success metrics—identify trends, surface insights, recommend course corrections
• Create compelling data stories —translate metrics into business impact narratives that demonstrate the value of AI investments
• Maintain visibility dashboards —build and maintain executive-level views of AI portfolio health, ROI, and strategic alignment
• Drive accountability —ensure teams are tracking the right metrics and making data-informed decisions throughout the product lifecycle

Drive AI Adoption and Evangelism (Ongoing)

• Educate and inspire stakeholders across the organization—show what's possible, demystify AI, build excitement and trust
• Create compelling storytelling around AI wins—showcase ROI, member impact, operational improvements
• Build internal AI literacy —run workshops, create documentation, empower teams to think about AI opportunities
• Stay on the cutting edge —monitor AI trends, tools, and best practices; bring fresh ideas to the table

Growth and Career Trajectory

This role offers significant growth potential as the AI Center of Excellence matures. As you demonstrate impact and expand the scope of AI initiatives, opportunities will emerge to:

• Scale your influence —take ownership of larger, more strategic AI programs that span multiple business units
• Shape organizational direction —become a key voice in enterprise-wide AI strategy and investment decisions
• Build and lead —as the CoE grows, there may be opportunities to build and mentor a team of AI product managers
• Advance your career —proven success in this role naturally positions you for Senior PM, Principal PM, or AI Product Leadership positions

We're looking for the right fit regardless of title—whether you're a strong mid-level PM ready to level up or an experienced senior PM excited to build something from scratch, we want to talk.

Qualifications

• 3-5+ years of product management experience, ideally with exposure to AI/ML, data products, or emerging technologies
• Proven track record of shipping 0→1 products—you've built something new from scratch and driven it to adoption
• Technical fluency—you understand how AI/ML works (models, training data, APIs, LLMs, etc.) and can have credible conversations with data scientists and engineers
• Strong strategic thinking—you can identify high-impact opportunities, prioritize ruthlessly, and build compelling business cases
• Experience with metrics and reporting—you're comfortable defining KPIs, building dashboards, analyzing performance data, and presenting insights to executives
• Healthcare or member-focused experience (preferred but not required)—bonus if you understand HIPAA, compliance, or regulated industries

Core Competencies

• Bias for action: You move fast, iterate, and don't wait for perfect information
• Comfort with ambiguity: You thrive in unstructured environments and create clarity from chaos
• Cross-functional leadership: You influence without authority and build strong partnerships
• Data-driven decision making: You use metrics and insights to guide your choices
• User-centric mindset: You start with member/user needs and work backward
• Communication skills: You can explain complex AI concepts to non-technical audiences, tell compelling data stories, and rally people around a vision
• Executive presence: You're comfortable presenting to senior leadership, reporting on progress, and advocating for resources

AI/ML Knowledge (You should be able to...)

• Explain the difference between supervised learning, unsupervised learning, and reinforcement learning
• Understand when to use predictive models vs. generative AI vs. rule-based systems
• Evaluate model performance (accuracy, precision, recall, F1 scores, etc.)
• Identify data quality issues and their impact on AI outcomes
• Articulate responsible AI principles (fairness, transparency, privacy, accountability)
• Navigate conversations about LLMs, prompt engineering, RAG, fine-tuning, and embeddings

Success Metrics (First 12 months)

• Ship 2-3 AI Products: Launch AI products/features to production with measurable member or business impact
• Establish Governance: Create AI governance framework adopted by product and engineering teams
• Build the Playbook: Develop AI product playbook used across the organization
• Demonstrate ROI: Show tangible ROI from AI initiatives (cost savings, revenue growth, member engagement, operational efficiency)
• Establish Reporting Cadence: Build executive dashboards and regular reporting rhythms for AI portfolio performance and strategic alignment
• Grow Your Influence: Become recognized internally as the AI product leader and trusted advisor to executive stakeholders

Why This Role is Special

• Ground-floor opportunity: You're not joining an established CoE—you're building it. Your decisions will shape how Tivity leverages AI for years to come.
• Executive visibility: You'll work directly with senior leaders who are invested in AI's success and report regularly on progress and impact.
• Impact at scale: Your work will touch millions of members and improve health outcomes.
• Career acceleration: This role is designed for growth—demonstrate impact and advance into senior product leadership positions.
• Cutting-edge work: You'll work with the latest AI technologies and apply them to real-world problems.

Key skills/competency

• AI Strategy
• Product Lifecycle Management
• Data Science Collaboration
• Stakeholder Engagement
• AI Governance
• Metrics & Reporting
• 0-1 Product Development
• Technical Fluency (AI/ML)
• Strategic Thinking
• Communication Skills