Senior Platform Engineer (AI Native)

Department: Software Engineering

Employment Type: Full Time

Location: Remote

Description

Key Responsibilities

• Lead the design, implementation and delivery of complex infrastructure projects. 
• Build and scale the infrastructure behind our AI workloads, including cost, API reliability and platform support for LLM-powered features.
• Debug the hard problems: cluster behaviour under load, service-to-service traffic, consumer lag on the event backbone, and database performance.
• Own the infrastructure-as-code estate, keeping drift visible and reconciled, and setting module standards the rest of the team builds against.
• Advance the delivery pipeline, including policy-as-code gates, progressive delivery, and changes that are tested, reviewed and auditable.
• Contribute to our internal AI tooling, including the MCP server and agentic workflows that remove operational toil.
• Engineer cost controls through right-sizing, reserved capacity and waste removal, measured against a baseline and advocate for targeted spend.
• Mentor peers through pairing, code review and knowledge sharing, growing their judgement rather than answering for them.
• Cover security and governance alongside the platform work in collaboration with the infrastructure team.

• Reduced time and manual effort in operational workflows, and improved speed, accuracy, cost or service quality across the business.
• Platform reliability and incident outcomes, including systemic fixes landed rather than repeat incidents patched.
• Complex infrastructure projects delivered end to end, with the decisions recorded and followable.
• Infrastructure-as-code and pipeline health, including drift reconciled and standards adopted by the wider team.

What we are looking for

• Strong software engineering. You write code you would be happy to maintain, in at least one language, and you can move between languages when the problem requires it. 
• Real production infrastructure ownership. You have been responsible for something running in production, on a major cloud, including when it broke.
• Infrastructure as code depth. You understand state, module design, and why reviewed, repeatable changes matter.
• Kubernetes in production. You have debugged a cluster that was misbehaving, not only deployed to a healthy one.
• CI/CD fluency. You have designed a pipeline, not only consumed one.
• Fluent, critical use of AI tooling. We build with AI but understand its limitations too and you will evolve with the tools as the industry transitions.
• You work well remotely - we’re fully remote with offices in multiple locations and we have an async-first mentality.
• Calm under pressure. When the platform is down and the company is watching, you communicate a plan and work the problem methodically, keeping people informed without being in the room.

• Experience in freight, logistics or supply chain, or in another B2B SaaS or operational technology environment.
• Experience building workflow automation or orchestration, for example with tools such as n8n.
• Experience our architectural setup e.g. with a service mesh, event streaming at scale or managed  Postgres-compatible databases under real load.
• Familiarity with infra-adjacent processes such as Identity and access management as a discipline, including SSO and secret management or SRE methodology.
• Building with LLM APIs, MCP servers or agentic tooling, rather than only using a chat assistant.