Principal AI Engineer - (Applied AI, Agents, LLMs

Our client is building a next-generation AI platform that delivers production-grade AI solutions across a broad portfolio of enterprise products and services.

They are seeking an exceptional Principal Engineer – Applied AI to provide technical leadership across AI architecture, large language models, agentic systems and enterprise AI platforms.

This is a senior individual contributor role for an engineer who enjoys solving complex AI engineering challenges, influencing technical strategy and helping engineering teams build reliable, scalable AI systems that deliver measurable business impact.

As Principal Engineer, you will define the technical direction for Applied AI across multiple engineering teams, shaping how modern AI technologies are evaluated, deployed and operated in production.

Working alongside Product, Platform, Research and Engineering leaders, you will guide architectural decisions, mentor senior engineers and establish engineering standards for enterprise AI development.

This role is designed for a hands-on technical leader who remains close to the code while influencing technology strategy across the organisation.

• Define the technical strategy for enterprise AI platforms and applications.
• Lead architecture decisions spanning LLMs, retrieval systems, AI agents and model deployment.
• Establish engineering standards and best practices for production AI systems.
• Evaluate emerging AI technologies and determine their suitability for enterprise adoption.
• Design scalable, secure and reliable AI architectures capable of supporting enterprise workloads.
• Guide the design and deployment of production AI solutions using modern AI frameworks and tooling.
• Drive architectural decisions relating to model serving, inference, retrieval pipelines and AI orchestration.
• Improve system performance, scalability, reliability and operational efficiency.
• Establish robust evaluation frameworks to measure model quality and business impact.
• Ensure AI solutions are designed with governance, security and operational excellence in mind.

• Remain actively involved in technical design, architecture reviews and engineering discussions.
• Build prototypes and reference implementations to validate architectural approaches.
• Solve complex technical challenges that span multiple engineering teams.
• Lead technical reviews, incident analysis and architectural governance.
• Support engineering teams in delivering high-quality production systems.
• Mentor Staff and Senior Engineers while helping develop future technical leaders.
• Establish engineering standards and promote a culture of technical excellence.
• Support senior technical hiring through interview design and candidate assessment.
• Encourage experimentation, innovation and continuous improvement across engineering teams.

• Partner closely with Product, Platform, Research, Security and Infrastructure teams.
• Translate complex technical concepts into clear recommendations for executive stakeholders.
• Contribute to long-term AI strategy and technology roadmaps.
• Collaborate with external technology partners and vendors where appropriate.

• 12+ years' experience in software engineering with significant experience delivering AI or machine learning systems.
• Proven success operating at Staff or Principal Engineer level within technology organisations.
• Deep expertise designing and deploying production AI systems.
• Strong understanding of Large Language Models, Generative AI and modern AI architectures.
• Experience leading technical strategy across multiple engineering teams.
• Strong mentoring experience with senior engineers and technical leaders.
• Excellent written and verbal communication skills.

Candidates should demonstrate deep expertise across several of the following areas:

• Retrieval-Augmented Generation (RAG)
• AI Agents and Agentic Workflows
• Prompt Engineering
• AI Governance

• Model Serving & Inference
• AI Orchestration Frameworks
• Vector Databases
• Evaluation Frameworks
• Production AI Infrastructure

• Python
• Distributed Systems
• API Design
• Microservices
• Cloud-Native…