About this role
Salary: £100,000 - 100,000 per year
Requirements: Demonstrated experience building or evaluating AI/ML-powered products, including familiarity with evaluation methodologiesUnderstanding 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 capabilitiesMastery of AI tools, in particular Claude Desktop and Claude Code, with day-to-day use to work faster while maintaining safety and responsible-use standardsMastery of AI Skills: authoring and applying reusable, packaged capabilities to extend and standardize AI tools and agent workflowsDemonstrated hands-on proficiency with AI-assisted development tools such as Claude Code or GitHub CopilotStrong analytical mindset with the ability to define evaluation frameworks, interpret metrics, and make data-driven product decisionsAbility to translate technical concepts into clear, value-based messaging for non-technical and senior audiencesDeep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiencyStrong experience using AI tools to lead innovation initiativesDemonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organizationBachelors/Masters/PhD degree in Computer Science, Engineering, Data Science, Business, or a related field Responsibilities: Own the product lifecycle for increasing AI integration across our business services and making our capabilities consumable by AI agentsMake our existing business services consumable by AI agents, defining how each capability is exposed and packaged for agent-based consumptionRecommend the best distribution channel for each business service, evaluating MCP, MCP App, and other options based on customer fit, reach, and technical trade-offsBuild prototypes to test in front of internal and external clients, validating fit before committing full engineering resourcesGather structured feedback from those tests to inform data-driven product decisionsHelp ensure every integration complies with legal and regulatory frameworks, partnering with Legal, Compliance, and Risk as neededHelp build and maintain the end-to-end evaluation framework for AI-integrated services, contributing to metrics, benchmarks, and acceptance criteria before each production deploymentDesign and maintain evaluation pipelines, ensuring accuracy, recall, and explainability standards are metDefine and track performance KPIs across latency, accuracy, hallucination rate, coverage, and user satisfaction, balancing quality, cost, and scaling requirementsDrive continuous improvement cycles based on evaluation results, customer feedback, and production monitoring dataContribute to the business case and OKRs for the domain, helping define value hypotheses and track benefits realization post-launchSupport product definition for MCP and MCP App integrations, enabling external AI systems to consume our capabilities via standardized interfacesHelp shape the MCP App surface area, leveraging the protocols new UI capabilities to deliver richer, interactive experiences directly within AI agents rather than text-only tool outputsDefine the MCP tool and resource surface area, determining how our capabilities are exposed and where an MCP App UI adds value over a standard tool callPartner with engineering to design, build, and iterate on MCP server and MCP App implementations, ensuring reliability, security, and compliance with data governance standardsValidate MCP and MCP App integrations through structured testing with partner AI systems and customer environmentsUse AI tools such as Claude Desktop and Claude Code to rapidly prototype capabilities, validate hypotheses, and accelerate delivery while keeping safetyAuthor and apply AI Skills to standardize and scale agent workflowsSupport solution discovery through customer engagements, beta and trial deployments, and design sprints that validate fit before committing full engineering resourcesWork embedded with engineering teams from concept through production, maintaining accountability for delivery timelines and qualityDocument architectures, evaluation results, and best practices to enable repeatability and scaleChampion the AI-First mindset across the segment, identifying opportunities to embed our AI capabilities into customer workflowsMentor peers on AI product practices, evaluation approaches, AI-assisted development, and AI Skills, contributing to the broader teams capabilityPartner with Pre-Sales on customer engagements, leading technical discovery sessions, demonstrations, and solution workshopsAlign with Commercial Strategy on market intelligence, competitive landscape, and go-to-market prioritiesCollaborate with Legal, Compliance, and Risk teams to ensure capabilities meet regulatory requirements and responsible AI standardsInteract with ML Engineering and Operations teams to ensure implemented solutions are enterprise-grade, meeting production standards for scalability, reliability, security, monitoring, and supportability Technologies: AIAI AgentsChatGPTClaude CodeCopilotEmbeddedExposedGitHubSupportMCPSecurityUX UI Design More:
We are partnering directly with Moodys Corporation to hire for this role. You will join the C&G Product Builders team, which unites product vision with engineering excellence to deliver solutions across our client base, including corporate and government. The team builds end-to-end, from data to AI agents and customer-facing analytics, operating in squads that own the full lifecycle from solution concept to production. This role is at the center of our push to make our business services consumable by AI, delivered across our platforms and external MCP channels including marketplaces, customer platforms, and foundational models like Claude and ChatGPT. With a strong growth mandate and global reach, our team offers a dynamic environment where rapid solution prototyping, deep technical collaboration, and ownership define how work gets done.
last updated 39 week of 2026