Principal Software Engineer-AI

Moody's Investors Service; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Moody's Investors Service is seeking a Principal Engineer to spearhead the strategy, delivery, and evolution of mission-critical AI platforms and intelligent applications within the Digital Content and Innovation organization.

You will lead, grow, and organize multiple engineering teams, drive architectural decisions, and ensure responsible AI governance while managing budget and vendor relationships to deliver measurable business impact at scale.

Qualifications

• 12+ years in software engineering with leadership roles.
• Experience guiding multiple teams and managers across a portfolio.
• Deep expertise in enterprise AI with LLMs and AI governance.

Responsibilities

• Define and execute long-term technical strategies for AI platforms.
• Lead multiple engineering teams with accountability for delivery.
• Drive AI-powered solution architecture using LLMs and orchestration.
• Establish engineering excellence through reviews, testing, observability, security.
• Own budgeting, cloud infra, tooling, and vendor relationships.
• Partner with stakeholders to maximize value and responsible AI governance.
• Develop engineering leaders through mentoring and succession planning.
• Define metrics for adoption, reliability, and cost efficiency.

Skills

Leadership experience

AI/ML systems

Cloud platforms

Multi-team leadership

LLMs & AI tooling

Architecture & reviews

Observability & SRE

Production AI

AWS/Azure

Data pipelines

Strategic roadmaps

Education

Bachelor's or Master's in CS/Engineering/AI

Tools

TypeScript

Python

C#

Job description

Skills and Competencies

• 12+ years of software engineering experience, including 5+ years leading engineering teams and delivering complex, large-scale, multi-team initiatives with measurable business impact
• Experience leading multiple teams or groups of teams, including managing engineering managers, technical leads, and staff-level engineers with accountability for delivery outcomes across a portfolio
• Strong technical depth in TypeScript, Python, C#, or similar technologies, with the ability to engage credibly in architecture and code reviews, challenge design decisions, and assess technical risk
• Deep expertise in enterprise AI applications built on large language models, including agents, retrieval augmented generation, orchestration frameworks, model optimization, and evaluation frameworks
• Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling)
• Experience running AI systems in production at scale, including observability, cost and capacity planning, regression detection, and incident response for AI-powered applications
• Experience operating production distributed systems on AWS/Azure, with a strong grasp of reliability, observability, and incident response at scale
• Deep knowledge of cloud-native technologies, serverless applications, event-driven architectures, data and inference pipelines, relational, NoSQL, and vector databases, and modern software architecture patterns
• Proven track record of owning multi-year technical strategy and architectural roadmaps, guiding teams from AI prototype through production deployment, and influencing organizational change
• 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

Education

• Bachelor's or master's degree in Computer Science, Engineering, Artificial Intelligence, or a related discipline, or equivalent professional experience

Responsibilities

Lead the strategy, delivery, and evolution of mission-critical AI platforms and intelligent applications while driving engineering excellence across the Digital Content and Innovation organization.

• Define and execute long-term technical strategies while owning the multi-year architecture and technology roadmap for AI platforms and applications
• Lead, grow, and organize multiple engineering teams, including engineering managers, technical leads, and staff-level engineers, with accountability for delivery outcomes across the portfolio
• Drive architectural decisions, organizational alignment, and integration of AI-powered solutions using large language models, retrieval augmented generation, orchestration frameworks, and agentic workflows
• Establish engineering excellence through architecture reviews, code reviews, automated testing, observability, security standards, operational excellence, and machine learning operations practices
• Own budget planning and cost management, including headcount, cloud infrastructure, model consumption, tooling investments, vendor relationships, and build-versus-buy decisions
• Partner with product, business, risk, legal, compliance, and audit stakeholders to maximize customer value and implement responsible AI governance practices
• Attract, develop, and retain engineering talent through mentoring, succession planning, performance coaching, and the cultivation of future engineering leaders
• Define and report on key metrics that demonstrate platform adoption, delivery performance, reliability, cost efficiency, and measurable business impact

About the Team

Our Digital Content and Innovation team is responsible for building and deploying intelligent, AI-powered solutions that drive innovation across Moody's products and platforms. The team accelerates the development of next-generation analytical capabilities, enables smarter client experiences, and advances Moody's leadership in applied artificial intelligence. As Principal Engineer, you will define the technical vision, guide strategic investments, build high-performing teams, and help transform applied AI into scalable, production-ready capabilities that deliver measurable value responsibly and at scale.