Lead AI Architect/AI Engineering Lead
Job Title: Lead AI Architect/AI Engineering Lead
Location: London, Edinburgh or Leeds
Salary: Up to £120,000 (working in London) + package (outlined below)
About the role:
Seeking an experienced Lead AI Architect/Engineer to own the end-to-end technical vision and delivery standards for generative AI and LLM-enabled systems. In this role, you will bridge hands-on Back End engineering with enterprise architecture, standardizing reusable AI patterns, establishing robust AWS infrastructure, and leading engineering teams to deploy scalable, secure, and production-ready AI solutions.
Key responsibilities:
- Architecture & Reusable Patterns: Establish end-to-end technical architectures for LLM-enabled systems (data pipelines, RAG, vector databases, prompt orchestration, agent workflows). Standardize reusable AI reference architectures to drive cross-team consistency and delivery quality.
- Governance & Enterprise Constraints: Analyse complex product, security, legal, operational, and regulatory constraints, translating them into clear engineering standards and recommendations for high-complexity AI deployments.
- DevOps, CI/CD & Operations: Enhance automated CI/CD pipelines, containerization, and controlled release practices tailored for AI systems. Define monitoring, observability, and cost/performance optimization strategies to maintain operational reliability and safety.
- Prompt Engineering & Evaluation: Set organizational standards for prompt design, guardrails, and rigorous evaluation/testing frameworks to ensure behavioural consistency, safety, and measurable quality metrics.
- Technical Leadership & Stakeholder Alignment: Lead engineering teams through technical guidance, code reviews, and enterprise architecture governance processes. Partner with senior stakeholders to deliver high-impact, analytics-led solutions that improve long-term business outcomes.
Minimum skill level:
- Extensive Back End engineering experience building production services (APIs, microservices) alongside solid software engineering fundamentals.
- Proven track record designing technical architectures and guiding them through enterprise review processes.
- Hands-on experience deploying, operating, and troubleshooting cloud solutions on AWS in live environments.
- Working knowledge of modern DevOps practices (CI/CD, containerization, monitoring) and agile, iterative delivery models.
Must have demonstrable experience in:
- AWS & AI Ecosystem: Direct experience building and operating solutions using AWS AI services (eg, AWS Bedrock) and supporting platform services in production.
- LLM & RAG Systems: Hands-on AI engineering experience delivering LLM systems utilizing LLM APIs, retrieval-augmented generation (RAG) architectures, vector databases, and orchestration frameworks.
- Engineering Leadership: Demonstrated experience leading engineering teams, aligning developers on architectural patterns, and resolving delivery or operational bottlenecks.
- Evaluation & Testing: Expertise in defining evaluation, guardrail, and testing frameworks for LLM solutions to measure quality, safety, and performance against defined success criteria.
Benefits include:
- 28 days annual leave plus bank holidays
- A minimum of 50% of their working time in the office each month
- Non-contributory pension (8-12% depending on age) and life assurance
- Private healthcare with Bupa, income protection
- 35 hours of paid volunteering annually
- A flexible benefits scheme designed around your lifestyle