Senior Platform Engineer - Internal Developer Platform

• A full-stack software engineering background (prerequisite): you've built and shipped production software yourself (e.g. in C#/.NET, Node.js, Python, Go or similar) - so you bring genuine developer empathy for the engineers you build the platform for, and you design self-service that you'd actually want to use.
• Senior-level experience: typically 5+ years building and operating cloud platforms or infrastructure, including owning a capability area end to end and setting patterns / mentoring other engineers.
• Cloud & Kubernetes: strong hands-on experience with Microsoft Azure (AWS/GCP transferable) and Kubernetes (AKS): networking, storage, managed databases.
• Infrastructure as Code & GitOps: Terraform and Helm; GitOps with ArgoCD or similar.
• CI/CD: modern pipelines (GitHub Actions ideal); experience migrating from other CI systems a plus.
• Observability & reliability: metrics/logs/traces, SLOs and error budgets; security/compliance as code (policy-as-code, secrets management, identity basics).
• Product mindset for internal tooling: developer empathy, self-service design, guardrails not gates.
• AI-First: you already work with AI coding assistants (e.g. Cursor) and are excited to build golden paths and agent workflows, not just consume them.
• Language: Professional-level English (spoken and written).

• API platform experience (Azure APIM, Apollo Federation/GraphOS) and developer-portal experience (Backstage).
• Exposure to agentic/LLM tooling, MCP, GitHub Spec-Kit, or building AI developer workflows.
• Interest or experience in Spec-Driven Development and AI coding assistants.
• Experience facilitating InnerSource or community-driven platform contributions.
• Familiarity with Team Topologies, DORA, SPACE / DX Core 4, CNCF platform maturity; workflow automation (n8n) and FinOps.

• We prioritise office presence and emphasise in-person collaboration, but also offer appropriate adjustments where needed, in line with company policy
• Extra wellbeing days on top of your annual leave allowance
• Up to 3 paid volunteering days each year
• 24/7 confidential Employee Assistance Programme (wellbeing, mental health, legal & financial support)
• Learning & development support via the Frontiers Learning Hub

At Frontiers, we are rewriting the rules of scientific publishing. To support our scale, we are transforming our Engineering Platform into a state-of-the-art Internal Developer Platform (IDP) built on modern principles and AI-augmented workflows - with a North Star of evolving it into an Agentic Development Platform (ADP) where human engineers and AI agents build software side by side, safely and at scale.

We are looking for a Senior Platform Engineer - Internal Developer Platform to help build and run that platform and the AI-First Delivery capabilities on top of it. This is the modern evolution of the DevOps Engineer role: you won't run a ticket queue - you'll treat the platform as a product, own a capability area end to end, and ship the golden paths, guardrails and automation that let our Stream-Aligned Teams (and their agents) deliver faster and more safely. You'll work closely with our Platform Product Manager and Senior Cloud Architect - turning platform strategy and prioritised needs into working capabilities.

Platform engineering gets more valuable in the AI era, not less: the platform does ~90% of the work, the model ~10%. You'll help move engineering effort from one-off delivery toward owning, running and evolving the platform and its agents - the scarce, high-leverage work of the next decade - all in service of a mission that matters: making science open for everyone.

• Build and operate the IDP: golden paths, self-service templates, the developer portal (Backstage) and IDP catalog, and guardrails that keep teams compliant by default (guardrails, not gates).
• Own CI/CD and GitOps: GitHub Enterprise and GitHub Actions; help drive the migration off Azure DevOps; implement GitOps (ArgoCD) for AKS - rethinking deployments rather than lifting-and-shifting custom tasks.
• Provision cloud infrastructure as code: evolve Azure (AKS, networking, databases, APIM, Key Vault, Entra ID) with Terraform and Helm; manage reliability and cost (FinOps).
• Improve observability & reliability: instrument systems (NewRelic, Grafana), define SLOs, reduce operational toil, and drive monitoring-cost accountability.
• Advance AI-First Delivery and the ADP: build agent-ready context (MCP, the Technology Framework), path definitions (e.g. validate-change, PR-review), and agent governance (non-human identity, sandboxed execution, evaluation, agent observability).
• Own a capability area end to end and set the standard: take a platform domain (e.g. CI/CD & GitOps, or cloud foundations) from design to run, define the reference patterns and ADRs others build on, and raise the bar through code review, mentoring and pairing.
• Build for adoption, like a product: design capabilities around real internal customers, write docs that work, and gather feedback from the teams you serve - so the platform is genuinely the easiest, safest path. Partner with the Platform Product Manager on priorities, and let adoption, DORA and DevEx metrics (not ticket counts) tell you what to improve next.

You will build and operate the capabilities that make up the IDP.

• Core Stack: Microsoft Azure, Kubernetes (AKS), containers (Docker); services in C#/.NET and Node.js.
• IaC & GitOps: Terraform, Helm, and a move toward GitOps with ArgoCD.
• CI/CD: Evolution from Azure DevOps toward GitHub Actions, modernizing pipelines (not a blind "lift and shift").
• Integration: Azure API Management, Apollo Federation/GraphOS, n8n.
• Security: Azure Entra ID, SonarQube, Azure Policy, Key Vault.
• Observability: NewRelic and Grafana (proactive SRE and business-value metrics).
• Developer Experience & AI: Backstage, our Technology Framework (policies/standards as executable AI context), MCP, and AI-driven development (e.g. Cursor AI, GitHub Spec-Kit).

• Adoption: teams/services on golden paths; self-service actions; time-to-first-deploy for a new service.
• Delivery (DORA): deployment frequency, lead time for changes, change-failure rate, time to restore.
• Developer experience: internal NPS/satisfaction, support-ticket trend, golden-path coverage.
• Reliability & cost: SLOs met; cloud and monitoring spend under control.