Product Manager

Role & Responsibilities:

• Strategic Roadmap Development:
• Define and execute the roadmap for reusable GenAI assets (e.g., copilot templates, APIs, UI kits, embedding services) to accelerate enterprise-wide AI adoption.
• Prioritize features and initiatives based on cross-functional demand, technical feasibility, reuse potential, and ROI.
• Collaborate with Product, Engineering, and Data Science teams to align GenAI development with business use cases.
• Pilot Coordination & Adoption:
• Lead cross-functional pilots to validate GenAI solutions, ensuring alignment with stakeholder needs and scalability.
• Track usage metrics (e.g., adoption rates, user feedback, performance KPIs) to iterate on asset libraries and drive continuous improvement.
• Develop frameworks for measuring the impact of GenAI assets on productivity, cost savings, and innovation.
• Stakeholder Management:
• Partner with business units (e.g., Engineering, Product, Operations) to identify high-impact GenAI opportunities.
• Act as the primary point of contact for internal teams seeking to integrate GenAI capabilities into their processes or products.
• Communicate progress, risks, and outcomes to executive leadership and technical teams.

• Governance & Scalability:
• Establish processes for asset lifecycle management, including versioning, documentation, and deprecation.
• Ensure compliance with ethical AI principles, security standards, and regulatory requirements.
• Optimize resource allocation (budget, tools, talent) to maximize the reuse and scalability of GenAI components.
• Industry Trends & Evangelism:
• Stay ahead of GenAI trends (e.g., LLM advancements, agentic workflows) to inform roadmap decisions.
• Champion AI-first thinking across the organization through workshops, demos, and training programs.

Skills & Expertise:

Required:

• 8- 12 years in program/project management, with 3+ years focused on AI/ML or GenAI initiatives.
• Proven experience in managing reusable technical assets (APIs, SDKs, templates) or platform products.
• Strong understanding of GenAI technologies (e.g., LLMs, RAG, embedding models) and their enterprise applications.
• Expertise in roadmap prioritization frameworks (e.g., RICE, MoSCoW) and agile delivery.
• Ability to translate technical capabilities into business value for non-technical stakeholders.
• Proficiency in tools like Jira, Confluence, or Asana for cross-team coordination.
• Data-driven mindset with experience in tracking adoption metrics and ROI analysis.
• Knowledge of AI ethics, security, and compliance standards.

Nice to Have:

• Certifications in AI/ML (e.g., AWS ML Specialty, Google Cloud AI Engineer) or PMP/Agile.
• Technical background in software engineering, data science, or MLOps.
• Experience with no-code/low-code AI tools (e.g., n8, Microsoft Copilot Studio).
• Familiarity with cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI).

Qualifications:

• Masters degree in Computer Science, Business Administration, or a technical field (or equivalent experience).
• Track record of managing large-scale AI/ML programs with measurable business impact.
• Exceptional communication skills for bridging technical and executive audiences.
• GSD (Get Stuff Done) attitude is critical.