Asst Dir-Product Manager

Skills and Competencies Demonstrated experience building or evaluating AI/ML-powered products, including familiarity with evaluation methodologies Understanding of large language models (LLMs) and generative AI concepts, including AI agents, prompt engineering, context management, and Model Context Protocol (MCP), including MCP Apps and their UI capabilities Mastery of AI tools, in particular Claude Desktop and Claude Code, with day-to-day use to work faster while maintaining safety and responsible-use standards Mastery of AI Skills: authoring and applying reusable, packaged capabilities to extend and standardize AI tools and agent workflows Demonstrated hands-on proficiency with AI-assisted development tools such as Claude Code or GitHub Copilot Strong analytical mindset with the ability to define evaluation frameworks, interpret metrics, and make data-driven product decisions Ability to translate technical concepts into clear, value-based messaging for non-technical and senior audiences Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization.

Bachelor's/Master's/PhD degree in Computer Science, Engineering, Data Science, Business, or a related field Responsibilities Own the product lifecycle for increasing AI integration across Moody's business services and making Moody's capabilities consumable by AI agents. Make existing Moody's business services consumable by AI agents, defining how each capability is exposed and packaged for agent-based consumption Recommend the best distribution channel for each business service, evaluating MCP, MCP App, and other options based on customer fit, reach, and technical trade-offs Build prototypes to test in front of internal and external clients, validating fit before committing full engineering resources Gather structured feedback from those tests to inform good, data-driven product decisions Help ensure every integration complies with the legal and regulatory frameworks in place, partnering with Legal, Compliance, and Risk as needed Help build and maintain the end-to-end evaluation framework for AI-integrated services, contributing to metrics, benchmarks, and acceptance criteria before each production deployment Design and maintain evaluation pipelines, ensuring accuracy, recall, and explainability standards are met Define and track performance KPIs across latency, accuracy, hallucination rate, coverage, and user satisfaction, balancing quality, cost, and scaling requirements Drive continuous improvement cycles based on evaluation results, customer feedback, and production monitoring data Contribute to the business case and OKRs for the domain, helping define value hypotheses and track benefits realization post-launch Support product definition for MCP and MCP App integrations, enabling external AI systems to consume Moody's capabilities via standardized interfaces Help shape the MCP App surface area, leveraging the protocol's new UI capabilities to deliver richer, interactive experiences directly within AI agents rather than text-only tool outputs Define the MCP tool and resource surface area, determining how Moody's capabilities are exposed and where an MCP App UI adds value over a standard tool call Partner with engineering to design, build, and iterate on MCP server and MCP App implementations, ensuring reliability, security, and compliance with data governance standards Validate MCP and MCP App integrations through structured testing with partner AI systems and customer environments Use AI tools such as Claude Desktop and Claude Code to rapidly prototype capabilities, validate hypotheses, and accelerate delivery while keeping safety Author and apply