Vista previa de la oferta
Asst Dir-Product Manager
lead · Technology / Software Development
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
- 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 AI Skills to standardize and scale agent workflows
- Support solution discovery through customer engagements, beta and trial deployments, and design sprints that validate fit before committing full engineering resources
- Work embedded with engineering teams from concept through production, maintaining accountability for delivery timelines and quality
- Document architectures, evaluation results, and best practices to enable repeatability and scale
- Champion the AI-First mindset across the segment, identifying opportunities to embed Moody's AI capabilities into customer workflows
- Mentor peers on AI product practices, evaluation approaches, AI-assisted development, and AI Skills, contributing to the broader team's capability
- Partner with Pre-Sales on customer engagements, leading technical discovery sessions, demonstrations, and solution workshops
- Align with Commercial Strategy on market intelligence, competitive landscape, and go-to-market priorities
- Collaborate with Legal, Compliance, and Risk teams to ensure capabilities meet regulatory requirements and responsible AI standards
- Interact with ML Engineering and Operations teams to ensure implemented solutions are enterprise-grade, meeting production standards for scalability, reliability, security, monitoring, and supportability