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.
Key ResponsibilitiesShape 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.
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