AI Principal Engineer

NatWest Group; London; Remote; GBP 90,000 - 120,000; Full time

Job summary

A major financial institution is seeking an AI Principal Engineer to define and drive the architectural vision for AI solutions across the organization. The ideal candidate will have extensive experience in software engineering, expertise with AI technologies, and leadership skills. This hybrid role includes responsibilities such as designing robust AI infrastructures and collaborating with various teams. Join us to innovate within the finance sector.

Qualifications

• Significant experience in software engineering and architecture.
• Expertise with large language models and generative AI APIs.
• Proven ability to lead engineering teams and influence decisions.

Responsibilities

• Define and drive the architectural vision for AI development.
• Design, build, and maintain scalable AI infrastructure.
• Collaborate with research, data scientists, and product teams.

Skills

Software engineering

Machine learning

Python

Java

AWS

Kubernetes

RESTful APIs

Data pipelines

Tools

Docker

Kafka

OpenAI GPT

Claude

Job description

Join us as an AI Principal Engineer

• This is an opportunity for a driven senior engineer to take on an exciting new career challenge that combines the core skills of a software engineer with specialised knowledge in AI to build intelligent systems that can solve complex problems and drive innovation within NatWest
• You'll play a pivotal role in the Wealth AI centre of excellence (CoE) team in architecting, building and maintaining a highly extensible, scalable and maintainable platform that offers effective, reliable, and ethical AI solutions.
• You'll gain valuable stakeholder exposure as you build and leverage relationships, as well as the opportunity to hone your technical talents

What you'll do

As an AI Principal Engineer, you'll help to define and drive the architectural vision for our team to build the foundational infrastructure, tools, and services that enable scalable, reliable, and efficient development and deployment of AI Assistant and Agentic solutions across the Wealth franchise and functions.

You'll also be:

• Designing, building, and maintaining scalable and robust AI infrastructure and platform services
• Responsible for the end-to-end delivery of services and features ensuring high quality and timely delivery
• Building tools and pipelines for prompt and context engineering, fine-tuning, evaluating, and monitoring of Large Language Models (LLMs)
• Collaborating with Machine Learning researchers, data scientists, and business journey product teams to understand user cases and deliver reusable platform capabilities
• Contributing to the development of platform UI components, libraries, and documentation to accelerate LLM adoption
• Working across the life cycle, from requirements analysis and design, through coding to testing, deployment and operations

The skills you'll need

You'll come with significant experience in software engineering, software design, architecture and machine learning, as well an understanding of how your area of expertise supports our customers.

Along with an expert technical skills in software engineer, testing and deployment, you'll also need previous experience with LLMs and generative AI APIs, such as OpenAI GPT, Claude, along with knowledge of prompt and context engineering techniques. You'll need experience with agentic AI or model evaluation framework and have proven ability to lead engineering teams and influence strategic decisions.

You'll also need:

• Strong programming skills in Python or Java
• Experience with cloud platforms such as, AWS, Azure, GCP and container orchestration, such as Kubernetes
• Experience working with vector databases and retrieval-augmented generation (RAG) architectures
• Experience building RESTful APIs for internal and external consumption
• Proven knowledge of web technologies and web security
• Experience with building and maintaining data pipelines with messaging systems such as Kafka and Active MQ
• DevOps knowledge including Docker, GitLab, ArgoCD, or similar tools for automation and deployment pipelines

Hours
35

Job Posting Closing Date:
09/09/2025

Ways of Working:Remote First