Senior DevEx Engineer - Infrastructure

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior DevEx Engineer - Infrastructure based in Canada. Take a leading role in shaping the internal developer platform that enables engineering teams to build, test, and deploy software safely and efficiently. You will own critical infrastructure capabilities, including CI/CD pipelines, deployment workflows, self-service tooling, and ephemeral environments. A key focus will be defining how AI coding agents can integrate into everyday engineering workflows to improve productivity, speed, and reliability. You will use measurable engineering performance indicators to identify bottlenecks and drive continuous improvement. Working across a highly autonomous, distributed engineering organization, you will influence technical standards and mentor other engineers. This is an opportunity to combine infrastructure expertise, software engineering, and emerging AI technologies in a fast-paced environment where you can shape the role's direction.

You will own the systems and engineering practices that help development teams deliver reliable software while improving the overall developer experience. Your responsibilities will include: Own the internal developer platform end to end, including CI/CD pipelines, build and deployment workflows, canary and blue-green releases, self-service tools, and ephemeral environments. Design and implement AI-enabled development workflows, building tools and automation that help engineers collaborate effectively with coding agents while maintaining speed, quality, and safety. Measure developer productivity and software delivery performance, identify bottlenecks, and implement improvements based on data rather than assumptions. Take operational ownership of the infrastructure you build, ensuring reliability and participating in the Core Infrastructure on-call rotation. Define technical direction and establish engineering standards for how teams build, configure, test, and deploy services. Mentor less experienced engineers and promote sound engineering practices across the organization. Collaborate with product engineering teams to improve developer tools, frameworks, internal APIs, and the overall experience of building and maintaining applications. Develop and maintain standardized development pathways, reducing repetitive application boilerplate and providing reliable, well-supported tooling for common engineering tasks. Share technical decisions, trade-offs, and learnings transparently across a fully distributed team. Continuously explore opportunities to improve infrastructure efficiency and integrate emerging AI capabilities into engineering workflows. Requirements: The ideal candidate combines strong cloud infrastructure and platform engineering expertise with a genuine software engineering background. They should be comfortable taking ownership of production systems, working autonomously, and navigating evolving technical challenges. Key qualifications include: Strong experience with cloud infrastructure, preferably AWS; substantial experience with Google Cloud Platform (GCP) is also considered. Hands-on experience with Kubernetes in production environments. Practical infrastructure-as-code experience using Terraform, Pulumi, CloudFormation, Ansible, or a comparable solution. Terraform is preferred but not mandatory. Strong CI/CD expertise, including ownership of build, test, deployment, and preview-environment workflows. Experience measuring and improving software delivery performance using DORA, SPACE, or similar engineering productivity frameworks. Demonstrated ability to operate production systems, troubleshoot incidents, and participate in an on-call rotation. A solid software engineering background, including building and maintaining applications or products rather than focusing exclusively on infrastructure tooling. Strong understanding of developer experience and code ergonomics, with the ability to create tools and workflows that engineers find practical and intuitive. Excellent asynchronous communication skills and the ability to collaborate effectively within a remote, geographically distributed team. A proactive, independent approach to problem-solving, with the ability to manage work from initial discovery through implementation and production ownership. Comfort working in an environment where priorities evolve, requirements may be ambiguous, and technical direction must often be established through experimentation. Additional experience that would be advantageous includes: Hands-on experience with AI development tools, coding agents, or large language model (LLM)-based engineering workflows. Familiarity with Model Context Protocol (MCP) servers and agent integration patterns. Experience in payments, fintech, or other regulated industries. Benefits: Remote-first work: A fully distributed working environment designed around autonomy and effective asynchronous collaboration. Competitive compensation: A competitive compensation package; a specific salary range is not provided. Equity: Competitive share options. Flexible time off: Flexible holiday arrangements, with a minimum of 25 days to be taken. Home office support: £500 toward setting up your home office. Coworking access: Access to coworking spaces across major cities. Team gatherings: Workations and an annual company retreat to strengthen relationships and collaboration. Equipment: High-quality equipment suited to your role. Learning and development: A generous learning budget to support ongoing professional growth. Healthcare: Private medical insurance. Additional perks: Other benefits may be available depending on location. Inclusive workplace: A commitment to equal treatment, diversity, and an inclusive working environment.