# Developer Experience - Engineering Manager at Ebury > Spain · Manager · Engineering management · open. Source: https://alderhq.app/jobs/greenhouse%3Aebury%3A4966858101 (read 2026-11-14). ## Facts (observed) - Company: [Ebury](https://alderhq.app/companies/ebury) - Location text: Madrid; Madrid; Málaga - Where it can be done from (inferred): Spain (evidence: "Location: Madrid; Madrid; Málaga") - Posted: 2026-09-10 (65 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-13 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://job-boards.eu.greenhouse.io/ebury/jobs/4966858101 - Skills listed (inferred): AWS, GCP, Kubernetes, Terraform ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Spain, n 6): p25 €79k, median €83k, p75 €87k ## Description (the employer's text) Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed. If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future. Engineering Manager, Developer Experience (Platform & AI) Location: Madrid Work Model: Hybrid (4 days in-office / 1 day WFH) ### About the Team The Developer Experience (DevExp) team builds and operates the foundational platform powering all engineering at Ebury—from CI/CD, deployment, and test infrastructure to self-service tooling and enterprise AI systems across the development lifecycle. We treat our development process as a product, our engineers as customers, and success as measurable outcomes: lead time, change failure rate, and platform adoption. Our North Star is simple: driving modern SDLC evolution, scaling AI adoption safely, and maximizing developer autonomy across the business. ### About the Role You will lead this team as a player-coach. You will hire, mentor, and grow a team of platform engineers while staying technically grounded enough to drive direction on platform architecture, progressive delivery, and AI agent execution frameworks. You will own two core mandates end-to-end—from design and architectural strategy through to day-to-day operations: The Delivery Platform (CI/CD & Infrastructure) The AI-Assisted Developer Platform ### In This Role, You Will ### Own the Delivery Platform Run CI/CD as a Product: Define and deliver against strict SLOs for the SDLC platform. Continuously innovate and propose infrastructure improvements based on developer feedback. Build Progressive Delivery into the Paved Path: Implement automated canary releases, real-time metric analysis, instant rollbacks, feature flag management, and safe database migrations across our AWS and GCP environments (Kubernetes, ECS/EKS). Evolve Observability & Self-Service Infrastructure: Provide developer self-service tooling in partnership with product engineering, including automated service scaffolding, a centralized software catalog with ownership scorecards, ephemeral PR preview environments, and standardized Terraform modules. Elevate Quality Gates: Maintain shared test infrastructure and automated quality guardrails to keep change failure rates low—even as overall code volume grows through AI-assisted engineering. ### Build the AI-Assisted Developer Platform Operate Ebury’s Agent Harness: Build and run managed, sandboxed execution environments for coding agents (Claude CLI, Gemini CLI, and emerging successors) featuring isolated Git worktrees, short-lived scoped credentials, session audit logs, and multi-model routing to prevent vendor lock-in. Integrate AI Where It Pays Off: Deploy evaluated AI tooling into the SDLC for pull-request reviews, test generation, automated dependency/code migrations, internal docs, and incident summarization. Build Context Layers for Agents: Expose internal context via Model Context Protocol (MCP) servers over our software catalog, engineering standards, runbooks, ADRs, and internal docs. Implement Financial-Grade Guardrails: Engineer strict security guardrails tailored to a regulated financial institution, including sandboxed execution with egress controls, prompt-injection defenses, human-in-the-loop approval gates, and eval suites to prevent AI behavioral regression. Instrument the Entire SDLC: Track traditional DORA metrics alongside AI-specific telemetry (adoption rate, suggestion acceptance/reversal rates, agent session success, and review overhead). ### Lead and Scale the Team Hire & Coach: Recruit, grow, and retain high-performing platform engineers while remaining hands-on enough to review designs and unblock technical obstacles. Lead with Evidence: Drive the product roadmap using developer research, adoption metrics, and satisfaction surveys rather than reactive ticket queues. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aebury%3A4966858101 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.