Platform Engineer
First seen by Alion on Aug 14, 2026.
Key Responsibilities:
- Design & Build Cloud Platforms: Architect and implement scalable, secure, highly available cloud-native platforms across AWS, GCP, or Azure, including Kubernetes, networking, identity, and multi-tenancy.
- Lead Platform Engineering Initiatives: Own complex, multi-month platform projects end-to-end, from architecture and technical design through implementation, production rollout, and continuous improvement.
- Develop Internal Developer Platforms (IDP): Build and enhance self-service platforms, tooling, and workflows that improve developer productivity, standardisation, and overall developer experience.
- Drive Infrastructure as Code & GitOps: Establish and standardise infrastructure and deployment practices using tools such as Terraform/Pulumi and ArgoCD across engineering teams.
- Build AI/ML Infrastructure: Design and operate infrastructure supporting model serving, inference pipelines, GPU workloads, and LLM integrations, ensuring scalability, reliability, and performance.
- Ensure Security & Compliance: Embed security, governance, and compliance best practices across the platform, aligning infrastructure with frameworks such as SOC 2, ISO 27001, and GDPR.
- Optimise Platform Cost & Performance: Drive FinOps initiatives and optimise cloud/GPU resource utilisation, particularly for large-scale AI/ML and inference workloads.
- Technical Leadership & Documentation: Create design documents and ADRs, communicate architectural decisions clearly, manage technical risks, and collaborate with engineering and business stakeholders to establish long-term platform strategy.
Requirements:
- 5 to 8 years in platform, infrastructure, or SRE with at least 3 years focused on cloud infrastructure or developer platforms.
- Expertise in cloud-native architecture: Kubernetes at scale, managed cloud services, networking, identity federation, and multi-tenancy patterns across AWS, GCP, or Azure.
- Proven ownership of complex, multi-month platform initiatives youve been part of them from whiteboard to production, managing ambiguity and technical risk throughout.
- Proficient in IaC and GitOps fluency Terraform or Pulumi, ArgoCD with experience standardising platform tooling and deployment patterns across engineering teams.
- Hands-on experience with AI/ML infrastructure: model serving, inference pipelines, GPU resource management, or LLM integration patterns.
- Experience in enterprise environments with familiarity with compliance frameworks such as SOC 2, ISO 27001, or GDPR.
- Strong written communication you write clear design docs, maintain useful ADRs, and can explain architectural decisions to both engineers and non-technical stakeholders.
Nice to Have:
- You treat platform as a product and obsess over internal developer experience.
- FinOps or GPU cost optimisation across large inference workloads.
- You default to writing things down and creating shared technical context.
- Building an internal developer platform (IDP) from scratch.
- LLM serving at scale vLLM, Triton, Ray Serve or AI gateway design patterns.
- You push back on short-term thinking and advocate for the right long-term call.
- Open-source contributions to platform or ML infrastructure tooling.
- Youre energised by ambiguity and build clarity where there isnt any.
Skills
DevOps, Kubernetes, AWS, Terraform, Azure, Google Cloud Platform, Cloud Services, IT Infrastructure Automation, Site Reliability, Cloud Infrastructure