Staff Software Engineer - AI

• We design, code, and lead delivery of scalable AI platforms and intelligent applications that bring emerging AI capabilities into production.
• We act as hands-on technical leaders, spending significant time designing, coding, reviewing, debugging, and improving production systems that support AI-powered products and services.
• We 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.
• We implement advanced large language model applications using retrieval-augmented generation, prompt orchestration, evaluation frameworks, model optimisation, agentic workflows, and tool integration.
• We make key technical decisions while remaining accountable for practical implementation quality, including code maintainability, system performance, reliability, security, scalability, and cost efficiency.
• We establish engineering best practices through hands-on contribution, code reviews, technical design reviews, automated testing, observability, monitoring, and operational excellence.
• We champion machine learning operations practices including model lifecycle management, prompt versioning, automated evaluation, deployment pipelines, monitoring, and continuous improvement.
• We partner with product managers, data scientists, machine learning engineers, engineering leaders, and business stakeholders to translate strategic priorities into robust, buildable technical solutions.
• We build reusable frameworks, libraries, developer tooling, and platform components that accelerate AI development across multiple teams without creating unnecessary abstraction or complexity.
• We evaluate emerging AI technologies through practical prototypes, proof-of-concept builds, and production-readiness assessments, then guide teams on implementation patterns and trade-offs.
• We mentor engineers through practical technical coaching, pairing, code reviews, design feedback, documentation, and example-setting as a senior individual contributor.

Technologies:

• AI
• AI Agents
• Azure
• Backend
• Cloud
• Docker
• Support
• Java
• Kubernetes
• Machine Learning
• MongoDB
• PostgreSQL
• Python
• Redis
• Security
• TypeScript
• Web

More:

We are Moodys Corporation, a global leader in ratings and integrated risk assessment, and we are transforming how the world sees risk by advancing AI that moves from insight to action. Our Innovation team builds next-generation internal and external products powered by large language models, AI agents, machine learning, and natural language processing. We work collaboratively across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while shaping reusable platforms, frameworks, and responsible AI practices. We offer an inclusive environment where curiosity, innovation, knowledge sharing, and continuous growth are valued, and we invite talented candidates to apply even if they do not meet every requirement.

• We require 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.
• We require 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.
• We require 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.
• We require proven ability to take complex AI solutions from prototype to production, making practical engineering trade-offs across performance, scalability, reliability, security, maintainability, and cost.
• We require 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.
• We require 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.
• We require 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.
• We require deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation, platform scalability, and operational efficiency.
• We require demonstrated commitment to responsible AI practices, including AI risk awareness, ethical use, governance, evaluation, monitoring, and continuous improvement of AI-enabled products and services.
• We require a bachelors degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience.