Lead Cloud Platform Engineer, AI Platform

Lead Cloud Platform Engineer, AI Platform

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Doist

At a Glance

  • Tasks: Lead the design and operation of a cutting-edge cloud platform for AI products.
  • Company: Join i.AI, an innovative incubator focused on transforming AI in the public sector.
  • Benefits: Enjoy competitive salary, hybrid working, generous leave, and professional development opportunities.
  • Other info: Collaborative environment with career-defining projects and growth opportunities.
  • Why this job: Make a real impact on AI systems while shaping the future of cloud technology.
  • Qualifications: Hands-on experience with cloud platforms, strong technical leadership, and a passion for AI.

The predicted salary is between 60000 - 80000 £ per year.

Overview

Lead Cloud Platform Engineer role at i.

AI (Incubator for AI) to help design, build and operate the cloud platform that powers AI product delivery.

This is a hands-on technical leadership position focused on modern cloud infrastructure, security, and scalable platform capabilities to enable production AI systems in government contexts.

The role offers high autonomy within a flat engineering structure and opportunities to shape platform direction with strong engineering judgement.

Responsibilities

  • End to end platform engineering: own the technical delivery of platform initiatives from concept through to production, making architectural decisions and building secure, scalable cloud components that teams can depend on.
  • Platform as a product: design capabilities that improve the developer experience, creating reusable patterns for local development, pipelines, environments, observability, and operational ergonomics to accelerate shipping with less friction.
  • AI workload enablement: support production AI systems and agentic workloads; build and maintain platform capabilities for model access, routing, tracing, evaluation, reliability, and cost control.
  • Intelligent automation and security: treat security as a first-class concern with automated controls for software supply chain security, secrets management and policy as code; use Gen AI to reduce operational toil, introduce intelligent guardrails, and streamline developer workflows.
  • Technical leadership: shape platform direction through engineering judgement and hands-on delivery, mentor engineers, promote better patterns, and balance needs of individual teams with platform-wide coherence.
  • What you will thrive on
  • Strong hands-on experience building and operating production cloud platforms, with AWS preferred.
  • Deep understanding of platform architecture, distributed systems, networking, and reliability concepts (SLOs, tracing, alerting).
  • Interest in applying Gen AI/LLM tooling to reduce operational work and improve resilience.
  • Experience embedding security into delivery workflows, including software supply chain security, IAM, threat modelling, and policy as code.
  • Experience supporting AI/ML systems in production (model serving, MLOps, agentic orchestration, or prompt/inference cost trade-offs).
  • Proficiency in software development and infrastructure automation; track record of reusable patterns and engineering standards.
  • Strong ownership, judgement, and ability to operate in a flat, high-agency team; product mindset with emphasis on developer experience.
  • Ability to coach others and raise technical standards.

What we offer

  • Career-defining projects with outsized impact and opportunities to apply technology to transform the public sector.
  • Access to frontier models, compute resources, and a supportive, mission-driven team.
  • Growth and empowerment: learning and development 5 days off, annual stipends, conference funding, and opportunities to own important products early.
  • Life and family benefits: hybrid working in London, Manchester, or Bristol with occasional remote work abroad, generous leave, parental leave, and pension contributions.
  • Our stack
  • Cloud infrastructure: AWS (ECS, Lambda, Cloud Front, RDS, S3) with multi-cloud patterns across Azure and GCP.
  • Containerisation and delivery: Docker, container orchestration, Git Hub Actions, and deployment patterns (rolling, canary, blue-green).
  • Development: Terraform, Python with Fast API, Java Script/Type Script with Next. js, Astro, Node. js.
  • AI platform layer: tooling for model routing, tracing, evaluation (Lite LLM, Langfuse) with Lang Graph, DSPy, Inspect.
  • AI harness: Open Code and Claude Code; access to frontier models from Open AI, Anthropic, Google.
  • Observability: AWS Cloud Watch, Grafana, Sentry, X Ray.
  • Security: SAST, SCA, SBOMs, policy as code, CSPM, DAST, and automated IAM/secrets management.
  • Selection Process
  • UK government clearance process with sponsorship if needed.
  • Stages include a short initial conversation, technical take-home test, and multiple interviews with the team and senior representation.
  • Diversity and Inclusion information and privacy notices are provided as part of the process.

Salary: £69,675 — £90,756 GBP (GDAD role, with position within the grade range and non-pensionable allowances as applicable).

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Lead Cloud Platform Engineer, AI Platform employer: Doist

Brink's is an exceptional employer that fosters a collaborative and innovative work culture, empowering employees to drive global commercial strategies in the ATM lifecycle solutions sector. With a strong focus on professional development and growth opportunities, employees are encouraged to expand their skills while contributing to sustainable growth and operational excellence. Located in a dynamic environment, Brink's offers unique advantages such as a diverse team and the chance to build long-term partnerships with global customers, making it a rewarding place to advance your career.

Doist

Contact Details:

Doist Recruitment Team

We think you need these skills to ace Lead Cloud Platform Engineer, AI Platform

Cloud Platform Engineering
AWS
Platform Architecture
Distributed Systems
Networking
Reliability Concepts
GenAI/LLM Tooling