Staff Software Engineer - AI

Moody's Corporation; Greater London; On-site; GBP 110,000 - 170,000; Full time

Job summary

Moody's Corporation seeks a senior software engineer to design and deliver scalable AI platforms that advance risk assessment through enterprise AI solutions. You will contribute production code, lead technical reviews, and mentor engineers while collaborating across product and data science teams.

The role emphasizes real-time and batch AI workloads, deployment automation, and responsible AI practices within a cloud-native environment. Moody’s fosters curiosity, integrity, and continuous growth.

Qualifications

• Experience designing, coding, testing, and operating scalable backend systems.
• Expert-level coding in Python, TypeScript, Java, Go, or similar languages.
• Experience building enterprise AI applications using LLMs, retrieval-augmented generation, and prompt engineering.
• Ability to balance performance, scalability, reliability, security, and cost in complex AI solutions.

Responsibilities

• Design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production.
• Hands-on technical leader: design, code, review, debug, and improve production systems.
• Design and build scalable backend services, APIs, data pipelines, and platform capabilities for real-time and batch AI workloads.
• Implement advanced LLM applications using RAG, prompt orchestration, evaluation frameworks, and model optimisation.
• Make key technical decisions with accountability for maintainable, secure, and efficient systems.
• Establish engineering best practices through reviews, automated testing, observability, and operations.
• Champion MLOps: model lifecycle management, monitoring, deployment pipelines, and continuous improvement.
• Collaborate with product managers, data scientists, ML engineers, and stakeholders to translate priorities into robust solutions.
• Build reusable frameworks and tooling to accelerate AI development across teams.

Skills

Backend system design

Cloud-native services

Python

TypeScript

Go

Java

LLM / AI applications

Prompt engineering

Distributed systems

Code review & mentoring

Education

Bachelor’s degree or higher in Computer Science, Software Engineering, AI, or related field

Tools

Docker

Kubernetes

PostgreSQL

MongoDB

Redis

Vector databases

Observability tools

CI/CD pipelines

AWS

GCP / Azure

Job description

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action - enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

Skills And Competencies

• 8+ years of experience 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 capability in modern programming languages such as Python, TypeScript, Java, Go, or similar, with the ability to personally contribute high-quality production code while guiding technical direction
• Deep hands-on expertise building enterprise AI applications using large language models, AI agents, retrieval-augmented generation, prompt engineering, orchestration frameworks, evaluation methods, and model optimisation techniques
• Proven ability to take complex AI solutions from prototype to production, making practical engineering trade-offs across performance, scalability, reliability, security, maintainability, and cost
• Expert knowledge of cloud platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure, with strong experience using Docker, Kubernetes, Elastic Container Service, or equivalent technologies in production environments
• Strong experience designing and implementing application programming interfaces, distributed systems, event-driven architectures, data pipelines, PostgreSQL, MongoDB, Redis, vector databases, observability, and automated deployment pipelines
• Demonstrated ability to influence technical direction while remaining close to the codebase, mentoring engineers through design reviews, code reviews, pairing, debugging, and hands-on problem solving
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation, platform scalability, and operational efficiency
• Demonstrated commitment to responsible AI practices, including AI risk awareness, ethical use, governance, evaluation, monitoring, and continuous improvement of AI-enabled products and services

Education

• Bachelor’s degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience

Responsibilities

Design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production

• Act as a hands-on technical leader, spending significant time designing, coding, reviewing, debugging, and improving production systems that support AI-powered products and services
• Design and build scalable backend services, application programming interfaces, data pipelines, inference pipelines, and platform capabilities that support real-time and batch AI workloads at enterprise scale
• Implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration
• Make key technical decisions while remaining accountable for practical implementation quality, including code maintainability, system performance, reliability, security, scalability, and cost efficiency
• Establish engineering best practices through hands-on contribution, code reviews, technical design reviews, automated testing, observability, monitoring, and operational excellence
• Champion machine learning operations practices including model lifecycle management, prompt versioning, automated evaluation, deployment pipelines, monitoring, and continuous improvement
• Partner with product managers, data scientists, machine learning engineers, engineering leaders, and business stakeholders to translate strategic priorities into robust, buildable technical solutions
• Build reusable frameworks, libraries, developer tooling, and platform components that accelerate AI development across multiple teams without creating unnecessary abstraction or complexity
• Evaluate emerging AI technologies through practical prototypes, proof-of-concept builds, and production-readiness assessments, then guide teams on implementation patterns and trade-offs
• Mentor engineers through practical technical coaching, pairing, code reviews, design feedback, documentation, and example-setting as a senior individual contributor

About The Team

Our Innovation team is responsible for building next-generation internal and external products powered by cutting-edge artificial intelligence technologies, including large language models, AI agents, machine learning, and natural language processing.

The group brings together engineers, data scientists, and AI specialists to solve complex challenges and turn breakthrough ideas into practical products that enhance productivity, unlock insights, and create measurable business impact.

Collaboration is central to how the team works. Engineers contribute across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while helping shape reusable platforms, frameworks, and responsible AI practices.

By joining the team, you will work on some of the most exciting challenges in applied AI, contribute directly to production code and architecture, and be part of a culture that values curiosity, innovation, knowledge sharing, and continuous growth

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.