Location
London

Hours
Full Time

Salary
Negotiable

About the Role
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities by fostering an inclusive environment where everyone feels welcome to be themselves, exchange ideas, and think innovatively. As a global leader in ratings and integrated risk assessment, Moody’s is advancing AI to move from insight to action—enabling intelligence that understands complexity and responds to it. We decode risk to unlock opportunity, helping clients navigate uncertainty with clarity, speed, and confidence.

We are seeking a Staff Software Engineer - AI to design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production across partner ecosystems. This hands-on technical leadership role involves significant coding, reviewing, debugging, and improving production systems supporting AI-powered products and partner integrations.

You will own the end-to-end technical architecture for the AI partner ecosystem, produce system diagrams, architecture documentation, and design standards aligning engineering efforts with product vision and stakeholder expectations. You will architect and evolve agentic workflows, skills, and tool-use integrations that allow AI systems to interact with Moody's platforms and third-party services via Model Context Protocol (MCP) and related protocols.

Responsibilities include implementing advanced large language model applications, building and delivering proofs of concept and prototype solutions, serving as a senior technical advisor in client and partner engagements, deploying and optimizing integrations across cloud environments, and championing responsible AI practices. You will also mentor engineers and collaborate with product managers, engineering leaders, and business stakeholders to translate strategic priorities into robust technical solutions.

Join a team responsible for building and deploying intelligent AI-powered solutions that drive innovation across products and platforms. Work on exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture valuing curiosity, innovation, knowledge sharing, and continuous growth.

Experience
8+ years in software engineering with deep hands-on experience designing, coding, testing, and operating scalable, resilient, production-grade backend systems and cloud-native services.
Expert-level coding skills in modern programming languages such as Python, TypeScript, or similar.
Deep expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation.
Proven ability to take complex AI solutions from prototype to production balancing performance, scalability, reliability, security, maintainability, and cost.
Experience with system integrations and modern interoperability protocols including Model Context Protocol (MCP) and agent-to-agent (A2A) standards.
Hands-on experience across major cloud platforms including Microsoft Azure, AWS, Google Cloud Platform, and Databricks.
Strong background designing APIs, distributed systems, event-driven architectures, and data pipelines.
Proven track record delivering technical proofs of concept, live demos, and prototype solutions.
Strong understanding of enterprise OAuth flows and secure authentication patterns.
Demonstrated ability to influence technical direction while remaining close to the codebase and mentoring engineers.
Commitment to responsible AI practices including risk awareness, ethical use, governance, evaluation, monitoring, and continuous improvement.
Excellent collaboration and communication skills with ability to lead architecture design and represent the organisation in external technical engagements.

About you
You are a hands-on technical leader passionate about AI innovation and production-grade engineering. You thrive in collaborative environments and enjoy mentoring and coaching engineers. You are committed to responsible AI and ethical technology use. You communicate complex technical concepts clearly to both technical and non-technical audiences and can influence product and engineering decisions effectively.

Qualifications
Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or related technical field, or equivalent practical experience.