Software Engineer - AI Platform & Agents

Salary: £64,000 - 104,000 per year

Requirements:

• 3+ years of experience in backend software development, building scalable, resilient, and production-grade systems
• Hands-on experience developing AI-powered applications, including large language models, AI agents, retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization techniques
• Proven ability to take AI solutions from concept and experimentation through to production deployment, optimizing for performance, reliability, scalability, and cost
• Strong knowledge of cloud platforms such as AWS, GCP, or Azure, along with containerization and orchestration technologies including Docker, ECS, and Kubernetes
• Proficiency with databases such as PostgreSQL and MongoDB and caching technologies such as Redis for high-performance data storage and retrieval
• Experience designing and building APIs, distributed systems, and event-driven architectures in modern programming languages such as Python, TypeScript, Java, Go, or similar
• Familiarity with MLOps practices, model monitoring, observability, versioning, and automated deployment pipelines preferred
• Strong problem-solving skills with the ability to navigate ambiguity, experiment rapidly, and deliver impactful solutions that create measurable business value
• Excellent communication and collaboration skills with demonstrated success working across multidisciplinary teams of engineers, data scientists, and product stakeholders
• Bachelors degree or higher in Computer Science, Software Engineering, or a related field

Responsibilities:

• Help shape the next generation of intelligent applications by building scalable platforms that bring cutting-edge AI capabilities into real-world production environments
• Design and build scalable backend platforms, APIs, and services that power AI applications, intelligent automation solutions, and AI agents
• Develop and deploy advanced LLM-powered applications using techniques such as retrieval-augmented generation, prompt engineering, evaluation frameworks, and model optimization
• Create robust data and inference pipelines that support both real-time and batch AI workloads at enterprise scale
• Partner with data scientists and machine learning engineers to integrate emerging AI capabilities into production products and services
• Build systems that enable AI agents to reason, automate tasks, interact with tools, and solve complex business challenges autonomously
• Optimize applications for performance, scalability, reliability, and cost efficiency while supporting increasing AI adoption and usage
• Implement engineering best practices around observability, monitoring, testing, security, and operational excellence
• Establish and champion MLOps practices including model lifecycle management, prompt versioning, automated evaluation, and continuous improvement
• Build reusable frameworks, developer tooling, and platform capabilities that accelerate AI innovation across multiple teams
• Participate in architecture discussions, technical design reviews, and engineering initiatives that influence the future direction of AI products
• Mentor engineers, share technical expertise, and contribute to a culture of innovation, experimentation, and continuous learning

Technologies:

• AI
• AI Agents
• AWS
• Azure
• Backend
• Cloud
• Docker
• GCP
• Support
• Java
• Kubernetes
• LLM
• Machine Learning
• MLOps
• MongoDB
• PostgreSQL
• Python
• Redis
• Security
• TypeScript

More:

We are Moodys, a global leader in ratings and integrated risk assessment, advancing AI to move from insight to action and help clients navigate uncertainty with clarity, speed, and confidence. Our Innovation team builds next-generation internal and external products powered by artificial intelligence, including large language models, AI agents, machine learning, and natural language processing. We work in agile, highly collaborative squads alongside engineers, data scientists, and AI specialists, with opportunities to contribute across the full AI lifecycle from experimentation and prototyping through to large-scale production deployment. We value curiosity, innovation, knowledge sharing, and continuous growth, and we are committed to creating an inclusive environment where everyone feels welcome to be who they are.

last updated 33 week of 2026