Lead Platform Engineer in Manchester

Are you a senior engineer who thrives on enabling teams to deliver faster, safer, and more consistently? Dizplai is seeking an experienced and hands‑on Lead Platform Engineer to join our growing engineering team. This is a senior, enablement-focused role where you'll shape and improve the shared platform capabilities that help our squads deliver with speed and confidence.

You'll lead the evolution of our AWS and engineering foundations, covering cloud infrastructure, account and environment management, deployment patterns, security guardrails, observability, automation, and developer experience. You'll combine deep technical expertise with broad organisational influence, helping set the direction for how we build, operate, and scale software reliably. A key part of this role is ensuring our organisation is set up to adopt AI safely, efficiently, and at scale. You'll define the right tooling, controls, reusable patterns, and platform standards so teams can use AI effectively without compromising security, quality, compliance, or cost.

This isn't about becoming a delivery bottleneck or gatekeeper. It's about enabling squads through strong reusable foundations, sensible standards, strategic platform leadership, and practical support.

• Shape Platform Strategy & Foundations: Define and drive the platform engineering strategy in line with business, technology, security, and delivery goals. Design, build, and evolve shared platform capabilities that support product and delivery teams, reducing duplication through sensible standardisation, automation, and internal platform tooling.
• Lead AWS Platform Enablement: Own and improve AWS platform patterns across accounts, environments, access models, and organisational guardrails. Define repeatable cloud approaches for infrastructure, identity, networking, secrets, compute, and storage, helping teams operate safely and efficiently without slowing delivery.
• Enable Safe, Fast Delivery at Scale: Improve the platform so squads can ship changes with greater speed and confidence. Support deployment patterns, release workflows, and engineering guardrails that reduce risk and improve consistency. Build self‑service capabilities where the preferred approach is the easiest to use.
• Enable AI‑First Engineering Safely: Create the platform foundations that allow teams to adopt AI effectively across engineering and operational workflows. Establish reusable approaches for AI services, model integrations, and agent‑based workflows, supporting safe and scalable AI usage through strong patterns for access, governance, and cost awareness.
• Strengthen Security, Observability & Operational Readiness: Improve platform standards across security, CI/CD, observability, reliability, and operational readiness. Embed secure‑by‑default and operable‑by‑default patterns into engineering workflows, improving logging, metrics, alerting, tracing, and production visibility across teams.
• Improve Developer Experience & Engineering Culture: Reduce friction in day‑to‑day engineering workflows by improving tooling, automation, templates, and platform usability. Promote a culture of enablement, shared ownership, and continuous improvement, helping embed a platform mindset where common problems are solved once and reused widely.

• Strong hands‑on experience in platform engineering, DevOps, cloud infrastructure, or SRE‑style work.
• Strong practical AWS experience across infrastructure, IAM, networking, deployment patterns, and environment management, including supporting AWS account structures, access models, and cloud guardrails across multiple teams or environments.
• Experience building and improving CI/CD pipelines, infrastructure as code, and shared engineering tooling.
• Good understanding of observability, monitoring, alerting, and production operations, alongside practical knowledge of security, secrets management, secure delivery, and operational controls.
• Experience improving developer experience, standards, or engineering workflows across teams, with a good understanding of how platform design can enable safe and efficient AI adoption.
• Experience influencing technical direction, engineering practice, or platform strategy across teams, with strong collaboration skills, technical judgement, systems thinking, and organisational awareness.

• Experience with AWS Organisations, multi‑account environments, Control Tower, and SCPs.
• Self‑service platform patterns and reusable internal templates.
• Reliability engineering, incident management, and FinOps practices.
• Enabling AI or ML tooling, model integrations, or LLM‑based workflows.
• Familiarity with Team Topologies and enabling‑team principles.