Principal Artificial Intelligence (AI) Platform Engineer/Architect

Ai-augmented Engineering
Reigate, United Kingdom
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Reigate, United Kingdom

Tech stack

JavaScript
A/B testing
API
Artificial Intelligence
Amazon Web Services (AWS)
Automation of Tests
Azure
Microsoft Online Services
C Sharp (Programming Language)
Cloud Computing
Code Generation
Continuous Integration
Programming Tools
Python
Performance Tuning
Systems Development Life Cycle
Runbook
TypeScript
Management of Software Versions
Delivery Pipeline
Large Language Models
Multi-Agent Systems
Prompt Engineering
Model Validation
Containerization
AI Platforms
Kubernetes
Machine Learning Operations
Api Design
Software Version Control
Data Pipelines

Job description

We are looking for an AI Platform Engineer to drive our vision of AI-augmented engineering across our enterprise of 500+ engineers. In this role, you will empower our highly skilled workforce to deliver high-quality value to our clients faster and with a better Developer Experience (DevEx) than ever before. We need someone who combines deep technical expertise with practical platform engineering to create the scalable infrastructure, processes, and tooling that enable our teams to integrate AI into their development workflows safely and seamlessly., Acting as both architect and hands-on builder, you will articulate our vision for AI-accelerated development practices, design platforms that embed AI at every phase of the SDLC, and champion adoption across our organization. We are seeking a highly skilled engineer who has recently specialized into AI technologies and can confidently guide our teams on both architecture and implementation., * Define and evolve the vision for AI-enabled SDLC practices, translating business and technical strategy into concrete platform capabilities and processes

  • Design and implement scalable AI platform infrastructure (SDKs, frameworks, deployment pipelines) that enables rapid, safe integration of AI into all phases of development-from coding and testing to deployment and monitoring
  • Build operational processes, templates, and playbooks that guide teams through AI implementation while maintaining consistency, quality, and auditability
  • Partner with teams across the organization to operationalize AI tools for SDLC acceleration (e.g., copilot-style code generation, test automation, documentation, performance analysis)
  • Create and maintain self-service tooling for model evaluation, prompt engineering, A/B testing, monitoring, and compliance validation
  • Establish and evolve patterns for data pipeline management, RAG/retrieval design, model versioning, endpoint management, and agentic orchestration
  • Develop comprehensive documentation, architectural guidance, runbooks, and examples that reduce onboarding time and accelerate team adoption
  • Evangelize AI-enabled practices through presentations, office hours, and direct team engagement-building credibility and driving adoption across the organization
  • Provide escalation pathways for architecture questions and unblock teams on complex integration challenges
  • Implement monitoring, observability, and governance systems that provide transparency without creating bottlenecks
  • Collaborate with security, compliance, and data teams to embed safety guardrails into platform capabilities
  • Participate in incident response and continuously harden the platform based on production learnings

Requirements

  • Extensive background in software or platform engineering across multiple SDLC phases (with a proven track record of leading large-scale, complex initiatives), with demonstrated expertise in infrastructure, developer tools, API design, or platform product development
  • Demonstrated, hands-on applied experience with LLMs, agentic frameworks, and GenAI systems (with proven hands-on experience)
  • Proven ability to design systems that abstract complexity and enable teams to self-serve at scale
  • Strong software engineering fundamentals (system design, testing, observability, operational excellence, SDLC practices)
  • Experience building or maintaining developer-facing platforms, SDKs, or internal tools
  • Comfortable articulating technical architecture, vision, and strategy to both technical and non-technical audiences

AI/ML & Ecosystem Knowledge

  • Hands-on experience with LLMs, agentic frameworks, and GenAI tooling (models, APIs, orchestration platforms)
  • Practical experience with RAG architectures, prompt engineering, fine-tuning workflows, and multi-agent systems
  • Experience with SDLC acceleration using AI (e.g., copilot-style tools, automated testing, code generation, documentation)
  • Familiarity with model deployment, versioning, inference optimization, and observability
  • Deep understanding of the rapidly evolving AI model and tooling landscape
  • Azure / Microsoft ecosystem experience advantageous but not mandated

Technical Skills

  • Proficiency in a range of languages, including Python, C#, JavaScript, or TypeScript
  • Experience with modern development practices (CI/CD, testing frameworks, containerization)
  • Extensive experience with cloud infrastructure (AWS, Azure, or GCP) and managed services
  • Strong problem-solving and systems thinking - able to design end-to-end solutions

Interpersonal & Influence

  • Exceptional communication skills with the ability to work across engineering, product, security, compliance, and leadership
  • Ability to present technical vision and architecture to both technical and non-technical audiences
  • Strong advocacy and influence skills - drive adoption through clarity, support, and relationship-building rather than authority
  • Empathy for developer experience; ability to understand and remove friction for end users
  • Comfort operating in ambiguity and rapidly evolving technical landscapes
  • Proven track record of building credibility within engineering organizations

Mindset

  • Initiative-driven: takes ownership of defining and evolving AI-enabled practices across the organization without needing a roadmap handed to them
  • Bridge-builder: comfortable spanning architecture, implementation, and team advocacy
  • Deeply committed to enabling others and multiplying team impact across 500+ engineers
  • Pragmatic - prefers safely shipping good solutions now over perfect solutions later
  • Learning-oriented - actively seeks to deepen AI knowledge while staying grounded in engineering fundamentals
  • Accountability - takes responsibility for platform reliability, team adoption, and driving measurable business outcomes

Benefits & conditions

Enjoy a benefits package designed to help you thrive, both professionally and personally. You'll receive 25 days of annual leave plus an extra WTW day to relax and recharge. Our comprehensive health and wellbeing offering includes private healthcare, life insurance, group income protection, and regular health assessments, all giving you peace of mind. Secure your future with our defined contribution pension scheme, featuring matched contributions up to 10% from the company.

We support your growth and balance with hybrid working options, access to an employee assistance programme, and a fully paid volunteer day to make a difference in your community. On top of these, you can opt into a variety of additional perks including an electric vehicle car scheme, share scheme, cycle-to-work programme, dental and optical cover, critical illness protection, and much more. Start making the most of your career and wellbeing with a range of benefits tailored for you.

Apply for this position