Principal Software Engineer-AI

Moodys; Greater London; On-site; GBP 64,000 - 104,000; Full time

Job summary

Moodys in the United Kingdom seeks a Principal Engineer to lead the strategy, delivery, and evolution of mission-critical AI platforms and intelligent applications, driving engineering excellence across the Digital Content and Innovation organization.

Define long-term technical strategies and multi-year roadmaps, lead multiple engineering teams including managers and staff engineers, guide architecture decisions for AI-powered solutions, and partner with product, risk, and legal to enable

Qualifications

• 12+ years of software engineering experience with 5+ years leading teams.
• Experience leading multiple teams including managers and senior engineers.
• Deep expertise in enterprise AI applications and LLMs.
• Bachelor's or Master's degree in CS/Engineering/AI or equivalent.

Responsibilities

• Lead strategy, delivery, and evolution of AI platforms.
• Define and execute multi-year architecture and technology roadmaps for AI platforms.
• Grow and organize multiple engineering teams with accountability for delivery across the portfolio.
• Establish engineering excellence through architecture reviews, code reviews, observability, security, and ML operations practices.

Skills

Technical leadership

AI platform experience

Cloud architecture

AWS

Azure

LLM / AI governance

Python

C#

Education

Bachelors or Masters in CS/Engineering/AI

Tools

MCP

Job description

Salary: £64,000 - 104,000 per year

Requirements:

• 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
• Bachelors or masters 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

Technologies:

• AI
• AWS
• Azure
• C#
• Cloud
• LLM
• Machine Learning
• MCP
• NoSQL
• Python
• RAG
• Security
• Serverless
• TypeScript

More:

Our Digital Content and Innovation team is responsible for building and deploying intelligent, AI-powered solutions that drive innovation across Moodys products and platforms. The team accelerates the development of next-generation analytical capabilities, enables smarter client experiences, and advances Moodys leadership in applied artificial intelligence. As Principal Engineer, we 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.

last updated 37 week of 2026