Role Summary:
We are seeking an AI Product Manager to lead strategy, roadmap, and delivery for AI-powered learning and development solutions across multiple product lines. This role spans custom client development, simulation design, AI-driven assessments, and enterprise-ready learning solutions aligned with the 4E Learn2Perform framework. You will work closely with cross-functional teams in a B2B SaaS environment to deliver scalable, client-focused solutions that meet diverse industry needs.
Key Responsibilities:
- Own the end-to-end product lifecycle across multiple AI-enabled learning solutions and simulations, from discovery to delivery.
- Lead custom client solutioninggather requirements, design tailored simulations or AI-enhanced learning modules, and ensure alignment with client objectives.
- Conduct client demos, proof-of-concepts, and pilot programs to drive adoption and showcase product capabilities.
- Collaborate with Sales, Pre-Sales, and Customer Success to scope and estimate projects for enterprise clients.
- Partner with Engineering & Design to define scalable AI architectures and ensure quality, performance, and compliance.
- Implement AI model evaluation frameworks to ensure accuracy, bias mitigation, and safety.
- Coordinate with Marketing to develop product narratives, case studies, and enablement material.
- Ensure seamless delivery in a B2B environment, balancing custom client requirements with core product roadmap priorities.
- Monitor product adoption, client feedback, and market trends to identify growth opportunities.
- Mentor junior product team members and contribute to building organizational AI product management best practices.
Requirements: 2-5 years of product management experience; at least 2 years working with AI/ML-enabled products.
- Proven experience in B2B SaaS or enterprise software, preferably in learning, simulations, or assessments.
- Strong understanding of AI concepts, including LLMs, retrieval-augmented generation, and AI evaluation pipelines.
- Ability to manage multiple concurrent projects across different clients and solution types.
- Exceptional stakeholder management, negotiation, and presentation skills in enterprise settings.
- Familiarity with L&D frameworks, learning science, or instructional design is an advantage.
Success Metrics:
- Client satisfaction scores (CSAT/NPS) for delivered solutions.
- Revenue from custom AI-enabled solutions and client renewals.
- On-time delivery rate for client projects.
- Product adoption and usage metrics across enterprise deployments.
- Reduction in AI model errors and latency.
Interested candidates and DM their resume to [Confidential Information]
