About the Role
We’re looking for a Senior DevOps / Platform Engineer for CipherScale’s AI-native platform to take independent ownership of the platform and release-engineering systems behind our continuous delivery model.
You’ll own the infrastructure, automation, and controls that govern how software is built, integrated, validated, and released. Your initial focus will be on strengthening trunk-integration safety, introducing robust release gates, isolating build and QA environments, and improving confidence across the entire delivery lifecycle.
This is not a ticket-execution role. You’ll set direction for the platform and release-engineering surface, establish the standards behind it, and work directly with engineers to remove delivery bottlenecks. You’ll be expected to identify foundational gaps, design pragmatic solutions, and take them through implementation, adoption, and operation.
We are an AI-native engineering organisation. AI agents and tooling perform a meaningful share of the implementation and operational work, and fluency with this way of working is essential. You’ll use AI to design systems, build automation, investigate failures, accelerate delivery, and continuously improve the platform.
Our philosophy is that we are a small, close-knit team, and we care deeply about you:
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Competitive pay rates
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Fully remote work environments
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Self-managed time off
Important:
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This will be a permanent employment opportunity for candidates based in Spain. For other locations, it will be a B2B contract.
Responsibilities
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Own the strategy, architecture, and operation of our platform and release-engineering systems
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Design and maintain scalable infrastructure using GCP, Cloud Run, infrastructure as code, and managed cloud services
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Own CI across a six-repository cluster, ensuring changes can be built, tested, integrated, and released safely at high velocity
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Build and operate the platform gates governing trunk integration, merge readiness, regression testing, and production releases
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Implement and maintain merge queues, GitHub rulesets, branch protections, required checks, and repository-level delivery policies
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Design isolated, reproducible review, build, integration, and QA environments
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Build release automation that supports progressive delivery, controlled rollouts, rapid rollback, and clear promotion criteria
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Improve build performance, test reliability, caching, dependency management, and CI resource efficiency
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Establish release observability, including deployment status, pipeline health, failure diagnostics, lead time, and change-failure metrics
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Create clear release-gating policies that balance delivery speed with product stability
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Partner with engineers to improve testability, deployment safety, and operational readiness
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Reduce manual intervention throughout the build, integration, and release lifecycle
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Investigate CI, environment, and release failures, lead root-cause analysis, and implement lasting corrective actions
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Apply secure-by-default practices to credentials, permissions, artefacts, dependencies, environments, and deployment workflows
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Define platform standards and documentation that improve developer autonomy and onboarding
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Use AI agents and AI-enabled engineering tools to build, operate, troubleshoot, and continuously improve platform systems
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Evaluate emerging AI-native approaches to release engineering, infrastructure management, testing, and operational automation
Day-One Mandate
Your initial mandate will be to take ownership of the platform gates and release pipeline, including:
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Establishing a reliable merge queue and trunk-integration model
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Defining integration and regression gates across the repository cluster
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Introducing isolated review and QA environments
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Strengthening GitHub rulesets, branch protection, and required-check policies
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Creating a consistent, automated release pipeline
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Implementing progressive delivery and rollback mechanisms
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Improving visibility into build, integration, and release health
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Prioritising and delivering the existing backlog of foundational platform work
Required Qualifications
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6+ years of experience in Platform Engineering, Release Engineering, DevOps, SRE, Infrastructure Engineering, or a closely related role
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Demonstrated experience independently owning a platform or release-engineering function
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Strong production experience with Google Cloud Platform, particularly Cloud Run and related managed services
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Deep experience designing and operating CI/CD systems using GitHub Actions
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Strong knowledge of GitHub rulesets, branch protection, required checks, merge queues, and Git-based delivery workflows
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Experience operating CI at scale across multiple repositories, services, or interdependent components
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Proven experience building release automation and progressive-delivery workflows Experience designing safe trunk-based development and continuous-delivery systems
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Strong understanding of build pipelines, test orchestration, artefact management, environment promotion, and rollback strategies
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Experience creating isolated preview, review, integration, or QA environments
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Strong knowledge of infrastructure as code and automated cloud provisioning
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Solid understanding of Linux, containers, networking, IAM, secrets management, and cloud security fundamentals
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Experience improving CI reliability, performance, reproducibility, and cost efficiency
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Ability to diagnose complex failures across source control, CI systems, cloud infrastructure, applications, and test environments
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Proficiency in at least one scripting or programming language, such as Python, Bash, Go, or TypeScript
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Strong written communication and the ability to define technical standards, explain trade-offs, and drive adoption
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Ability to work effectively with a Europe-based distributed team
AI-Native Working
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AI-native fluency is a non-negotiable requirement for this role.
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You should be comfortable using AI agents and tooling as part of your normal engineering
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workflow—not as an occasional assistant, but as a core part of how you deliver work.
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This includes using AI to:
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Design and evaluate platform architectures
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Generate, review, and improve infrastructure and pipeline code
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Build internal tooling and release automation
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Investigate CI failures and production issues
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Analyse logs, tests, deployments, and operational signals
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Create and maintain documentation
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Automate repetitive engineering and operational tasks
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Coordinate complex changes across multiple repositories
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Increase the speed and scope of your individual contribution
You’ll also help establish effective patterns for how AI agents interact with our repositories,
delivery systems, environments, and operational workflows.
Optional, but Good to Have
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Experience with Cloud Build, Artifact Registry, Pub/Sub, Workflows, Secret Manager, or other GCP platform services
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Experience with Terraform, Pulumi, or similar infrastructure-as-code tooling
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Familiarity with progressive-delivery platforms or techniques such as canary releases, traffic splitting, feature flags, or automated promotion
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Experience managing monorepos or tightly coupled multi-repository architectures
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Familiarity with contract testing, end-to-end testing, test-impact analysis, or selective CI execution
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Experience implementing ephemeral environments and automated environment lifecycle management
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Experience with container supply-chain security, software bills of materials, artefact signing, or provenance controls
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Familiarity with policy-as-code, dependency scanning, vulnerability scanning, and secrets detection
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Experience with observability tooling such as Google Cloud Monitoring, OpenTelemetry, Grafana, Datadog, or Sentry
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Experience defining and tracking delivery metrics such as deployment frequency, lead time, change-failure rate, and recovery time
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Experience building developer platforms, internal developer portals, or self-service engineering workflows
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Familiarity with AI coding agents, agent orchestration, model context protocols, or AI-enabled operational tooling
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Experience in a startup or other fast-moving product engineering environment
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Experience mentoring engineers or leading cross-functional platform initiatives
What Success Looks Like
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Within your first months, we expect to see:
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A clearly owned and prioritised platform and release-engineering roadmap
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Safer trunk integration with predictable, enforceable merge gates
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Reliable integration and regression testing across the repository cluster
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Isolated review and QA environments that can be created and removed automatically
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A consistent release process with progressive rollout and rollback support
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Faster, more reliable CI with fewer unexplained or intermittent failures
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Greater visibility into pipeline health, release status, and delivery performance
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Reduced manual intervention and increased developer confidence in continuous delivery
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Effective use of AI agents to accelerate platform development and ongoing operations
About CipherScale
CipherScale is building an AI-native Zero Trust security platform for a world where enterprise infrastructure is increasingly operated by humans and autonomous agents through natural language, agent protocols, and machine- to-machine capabilities.
- AI agents and agentic systems
- Model Context Protocol (MCP)
- Zero Trust, identity, and authorization
- Networking and distributed systems
- Cloud infrastructure and enterprise security
What We Offer
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Competitive salary and comprehensive benefits
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A senior ownership role with responsibility for a critical engineering surface
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The autonomy to define platform strategy, standards, and technical direction
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The opportunity to build foundational systems with immediate, measurable impact
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A fast-moving, AI-native engineering environment
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Direct collaboration with technical leadership and product engineers
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Support to experiment, automate, and introduce better ways of working
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A culture that values speed, ownership, sound judgement, and reliable delivery
