Staff Software Engineer - AI

Moody; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Moody’s is seeking a Staff Software Engineer - AI to lead the design and delivery of scalable AI platforms and intelligent applications. You will mentor engineers, drive production-ready AI solutions, and partner with cross-functional teams to translate strategic priorities into robust technical implementations.

You will work on cutting-edge AI technologies, including LLMs, retrieval-augmented generation, and orchestration, ensuring reliability, security, and cost efficiency across

Qualifications

• 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 in Python, TypeScript, Go or similar, with ability to contribute production code while guiding technical direction.
• Deep hands-on expertise building enterprise AI applications using LLMs, agents, retrieval-augmented generation, and model optimisation techniques.
• Proven ability to take complex AI solutions from prototype to production with performance, scalability, reliability and cost trade-offs.
• Expert knowledge of AWS/GCP/Azure with Docker, Kubernetes in production environments.
• Strong experience designing APIs, distributed systems, event-driven architectures, data pipelines, PostgreSQL, MongoDB, Redis, and observability.
• Ability to influence technical direction while mentoring engineers through reviews and hands-on problem solving.
• Deep expertise in AI with a track record of improving platform scalability and efficiency.
• Commitment to responsible AI practices including governance, monitoring, and ongoing improvement of AI-enabled products.

Responsibilities

• Design, code, and lead delivery of scalable AI platforms and intelligent applications bring AI capabilities into production.
• Act as hands-on technical leader, designing, coding, reviewing, debugging, and improving production systems supporting AI-powered products.
• Design scalable backend services, APIs, data pipelines, inference pipelines, and platform capabilities for real-time/batch workloads.
• Implement advanced LLM applications using RAG, prompt orchestration, evaluation frameworks, and model optimisation.
• Make key technical decisions with focus on maintainability, performance, reliability, security, and cost.
• Establish engineering best practices through code reviews, automated testing, observability, and operational excellence.
• Champion MLOps practices including model lifecycle management, prompt versioning, and deployment pipelines.
• Partner with product managers, data scientists, engineers to translate priorities into robust solutions.
• Build reusable frameworks and tooling to accelerate AI development across teams.
• Evaluate emerging AI tech through prototypes and POCs, guiding implementation choices.

Skills

Python

TypeScript

Go

AI/ML systems

Cloud platforms (AWS/GCP/Azure)

APIs & distributed systems

DevOps / CI/CD

Mentoring engineers

Responsible AI

Education

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

Tools

Docker

Kubernetes

Elastic Container Service

PostgreSQL

MongoDB

Redis

Vector databases

Job description

Let’s begin! Staff Software Engineer - AI (14399)

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.

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, 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.