Gen AI Product Owner - Whippany, NJ (Hybrid) - F2F interview Must

Role: Gen AI Product Owner

Locations: Whippany, NJ (Hybrid)

Duration: 12+ Months Contract

F2F Interview MUST For Local Candidates

Note: Candidate needs to be in the office 3-4 Days every week. Local or candidates from adjacent states only.

Product Strategy & Vision:

• Define and communicate the product vision, strategy, and roadmap for Generative AI products.
• Identify high-value business opportunities where Gen AI can improve efficiency, customer experience, or revenue growth.
• Translate business goals into actionable product requirements and AI use cases.
• Develop and maintain a prioritized product backlog aligned with organizational objectives.

Stakeholder Management:

• Collaborate with business leaders, technology teams, legal, risk, compliance, and operations teams.
• Act as the primary liaison between business stakeholders and AI development teams.
• Facilitate workshops to discover and prioritize AI use cases.
• Present product updates, insights, and performance metrics to executive leadership.

Product Delivery:

• Own the end-to-end lifecycle of Gen AI solutions from ideation through deployment and optimization.
• Define user stories, acceptance criteria, and product requirements.
• Partner with Scrum Masters and engineering teams during Agile delivery cycles.
• Ensure timely delivery of product releases and enhancements.

AI & Technology Oversight:

• Work with AI engineers and architects to evaluate LLM platforms such as:
• Azure OpenAI
• OpenAI
• Anthropic Claude
• Google Gemini
• AWS Bedrock
• Drive decisions regarding prompt engineering, RAG (Retrieval-Augmented Generation), AI agents, and knowledge management capabilities.
• Ensure AI solutions are scalable, secure, reliable, and cost-effective.

Governance & Responsible AI:

• Establish and enforce Responsible AI principles.
• Ensure compliance with security, privacy, regulatory, and ethical standards.
• Monitor AI model performance, bias, hallucination risks, and operational effectiveness.
• Define guardrails and governance frameworks for enterprise AI adoption.