Product Ownership & Strategy:

- Define and prioritize product roadmap for AI agents and automation tools, aligned with business objectives and client needs.

- Develop user stories, acceptance criteria, and success metrics in collaboration with stakeholders.

- Own the product backlog, balancing immediate business needs with long-term strategic goals.

- Conduct user research and gather requirements from Portfolio Services teams and clients.

Technical Deployment & Implementation:

- Lead end-to-end deployment of AI solutions into live Portfolio Services environments.

- Configure, customize, and integrate AI agents with existing systems and workflows.

- Troubleshoot technical issues during implementation and provide hands-on problem resolution.

- Build proof-of-concepts and MVPs to validate solution feasibility and business value.

Stakeholder Engagement & Change Management:

- Partner with Transaction Management, Lease Administration, and Consulting teams to understand pain points.

- Train end-users on new AI tools and capabilities, ensuring successful adoption.

- Gather post-deployment feedback and iterate solutions based on real-world performance.

- Communicate progress, challenges, and outcomes to leadership and cross-functional teams.

Governance & Quality Assurance:

- Ensure AI solutions comply with governance frameworks, security standards, and ethical guidelines.

- Document technical specifications, user guides, and deployment processes.

- Monitor solution performance and implement improvements based on usage data and feedback.

- Maintain quality standards throughout the development and deployment lifecycle.

Requirements:

- 10+ years of experience in Product Management, Software Engineering, Solutions Engineering, or Technical Implementation.

- Strong experience working with AI/ML solutions, automation platforms, or enterprise software deployments.

- Hands-on programming experience in Python, JavaScript, or a similar language.

- Good understanding of APIs, system integrations, and data workflows.

- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).

- Ability to work closely with customers to gather requirements, configure solutions, and drive successful deployments.

- Strong problem-solving skills with the ability to translate business needs into technical solutions.

- Experience collaborating with cross-functional teams, including Product, Engineering, and Customer Success teams.