Platform/DevOps engineer building and running Campbell Scientific's internal developer platform in the UK: GitOps delivery (Argo CD/Helm), Terraform and Ansible IaC, production Kubernetes across AWS and on-prem/bare metal, OpenTelemetry observability, supply-chain security, and AI-assisted engineering tooling so product teams can ship services easily and safely.
Compensation
Not disclosed
Location
Shepshed, United Kingdom
Work setup
Not specified
Seniority
Not specified
Employment
Not specified
Experience
Not specified
Category
Devops
Posted
Skills
ai
ansible
api
argocd
automation
aws
azure
bash
bitbucket
ci-cd
cloud
cybersecurity
developer-experience
devops
dns
docker
eks
fedramp
finops
firewall
gcp
github
github-actions
gitlab
gitops
grafana
helm
iam
infrastructure-as-code
iot
jenkins
kubernetes
loki
mqtt
nats
networking
nist
observability
openshift
opentelemetry
postgresql
prometheus
python
secrets-management
soc-2
terraform
timescaledb
tls
vault
vulnerability-scanning
zero-trust
Must have
Several years of experience in platform engineering, SRE, or DevOps, including production responsibility for Kubernetes and familiarity with K3s, Docker Swarm and OpenShift
Hands-on experience with GitOps (Argo CD), Helm, and CI/CD platforms such as GitLab CI, GitHub Actions, Bitbucket Pipelines or Jenkins
Strong infrastructure-as-code skills with Terraform plus configuration management with Ansible or similar
Solid experience with at least one major cloud provider (AWS preferred; Azure or GCP considered), including IAM, networking, and managed Kubernetes
Experience with eBPF-based networking and security (e.g., Cilium), service meshes, or multi-cluster management
Experience running workloads on-premises or on bare metal, including hardware lifecycle, persistent storage, and network integration
Experience restoring systems from point-in-time restore points and recovery from failure states (e.g. loss of storage quorum)
Programming and scripting ability in Go, Python, or Bash for automation, tooling, and Kubernetes operators or controllers
Working knowledge of networking and security fundamentals: DNS, TLS and certificate management, load balancing and ingress (incl. Kubernetes Gateway API), firewalls, zero-trust
Experience with secrets management such as HashiCorp Vault/OpenBao, AWS Secrets Manager, or External Secrets Operator
Experience building observability and alerting that teams actually use, preferably with OpenTelemetry
Nice to have
Experience building an internal developer platform or developer portal (e.g., Backstage)
Experience operating stateful and messaging workloads on Kubernetes (PostgreSQL/TimescaleDB operators, NATS, MQTT brokers)
Familiarity with compliance frameworks such as SOC 2, ISO/IEC 27001:2022, FedRAMP, and emerging product-security requirements such as the EU Cyber Resilience Act
At Campbell Scientific, we develop innovative measurement and monitoring solutions that help people understand and protect the world around us. From climate and environmental monitoring to renewable energy, infrastructure and scientific research, our technology supports organisations around the world in making better, data-driven decisions.
We are looking for an experienced Platform Engineer to join our team in the UK and play a key role in building and evolving the technology platform that enables our software teams to deliver secure, reliable and high-quality solutions. This is an exciting opportunity to work across cloud, Kubernetes, automation, DevOps and emerging AI technologies within a global technology-focused organisation.
Job Summary
We are seeking a Dev OpsPlatform Engineer to build and run the internal platform our product teams use to ship software safely and quickly, across public cloud and on-premises Kubernetes and Docker Swarm environments.
You will treat the platform as a product: its users are our developers, and success is measured by how easily they can build, deploy, observe, and operate their services without needing to become infrastructure experts.
The role spans GitOps delivery, infrastructure as code, Kubernetes operations, observability, and software supply-chain security. You will work closely with development, security, and operations teams, and help us use AI-assisted engineering tools responsibly within our platform workflows.
Key Responsibilities
Platform as a product: Build and maintain self-service "golden paths" (templates, reusable pipelines, and documented defaults) so teams can create, deploy, and operate services with minimal hand-offs. Gather developer feedback and track platform adoption and developer-experience metrics.
GitOps delivery: Design and operate declarative delivery using tools such as Argo CD and Helm, with progressive delivery (canary, blue/green) and automated rollback where appropriate. This includes providing solutions and documentation for consultants to manage air-gapped or isolated systems not directly managed by the DevOps team. This also includes creating immutable deliverables so that a release is completely defined and reproducible.
Infrastructure as code: Provision and manage cloud and on-premises infrastructure with Terraform, Ansible, and Kubernetes-native tools such as Crossplane or Cluster API. Keep environments reproducible, reviewed, and drift-free.
Kubernetes operations: Run production Kubernetes clusters in the cloud (e.g., Amazon EKS, K3s and OpenShift) and on bare metal, including upgrades, capacity planning, autoscaling, storage, networking, and the lifecycle of platform operators (databases, message brokers, certificates).
DevOps at Campbell Scientific Ltd. (Shepshed, United Kingdom) — aijobsearch
Docker Swarm orchestration: There are still some systems, including development environments built on Docker Compose/Docker Swarm functionality. These will need to be maintained and improved as work is done to migrate functionality into the standard platform. In some cases, Portainer is included in these environments.
Observability and reliability: Build observability on OpenTelemetry with metrics, logs, and traces (e.g., Prometheus/Mimir, Loki, Tempo, Grafana). Define SLOs and error budgets with service owners, run alerting and on-call, and lead blameless post-incident reviews.
Security and supply chain: Embed security into the platform by default: least-privilege and workload identity, secrets management, policy as code (e.g., Kyverno or OPA Gatekeeper), image signing and SBOMs (e.g., Sigstore/cosign), vulnerability scanning, and alignment with SLSA and the NIST Secure Software Development Framework.
Resilience and recovery: Design for high availability across zones and sites. Own backup, restore, and disaster-recovery procedures, and test them regularly.
Cost awareness (FinOps): Give teams visibility into what their workloads cost, right-size resources, and make cost a factor in platform design decisions.
Developer environments: Maintain fast, reproducible local and ephemeralt environments (e.g., Kind, Tilt, dev containers, or Nix) that match production closely.
AI-assisted engineering: Evaluate and integrate AI coding and operations assistants into platform workflows with appropriate guardrails, such as read-only production access, human approval for changes, and auditability.
Documentation and enablement: Keep architecture decision records, runbooks, and platform documentation current, and help teams adopt new platform capabilities.
Issue and manage customer licenses: Help implement, manage and maintain existing and new licensing systems to ensure customers have access to correct functionality and dependent software packages.
Required Qualifications
Several years of experience in platform engineering, site reliability engineering, or DevOps, including production responsibility for Kubernetes and familiarity with K3s, Docker Swarm and OpenShift.
Hands-on experience with GitOps (Argo CD), Helm, and CI/CD platforms such as GitLab CI, GitHub Actions, Bitbucket pipelines or Jenkins.
Strong infrastructure-as-code skills with Terraform plus configuration management with Ansible or similar.
Solid experience with at least one major cloud provider (AWS preferred; Azure or GCP considered), including identity and access management, networking, and managed Kubernetes.
Experience with eBPF-based networking and security (e.g., Cilium), service meshes, or multi-cluster management.
Experience running workloads on-premises or on bare metal, including hardware lifecycle, persistent storage, and network integration.
Experience restoring systems from point-in-time restore points and recovery from failure states (e.g. loss of storage quorum).
Programming and scripting ability in Go, Python, or Bash for automation, tooling, and Kubernetes operators or controllers.
Working knowledge of networking and security fundamentals: DNS, TLS and certificate management, load balancing and ingress (including the Kubernetes Gateway API), firewalls, and zero-trust principles.
Experience with secrets management such as HashiCorp Vault/OpenBao, AWS Secrets Manager, or External Secrets Operator.
Experience building observability and alerting that teams actually use, preferable with OpenTelemetry
Preferred Qualifications
Experience building an internal developer platform or developer portal (e.g., Backstage).
Experience operating stateful and messaging workloads on Kubernetes, such as PostgreSQL/TimescaleDB operators, NATS, or MQTT brokers.
Familiarity with compliance frameworks such as SOC 2, ISO/IEC 27001:2022, or FedRAMP, and with emerging product-security requirements such as the EU Cyber Resilience Act.
Experience with IoT or data-intensive platforms.
Relevant certifications (e.g., CKA, CKS, AWS Certified DevOps Engineer) are a plus but not required.
Product mindset: Treats developers as customers and makes decisions based on their feedback and measurable outcomes.
Automation and simplicity: Automates repeatable work, and prefers clear, well-documented solutions over clever ones.
Reliability ownership: Stays calm during incidents, communicates clearly, and follows through on fixing root causes.
Security by default: Makes the secure path an easy path rather than an extra step.
Collaboration: Communicates clearly in writing and in person across development, security, and operations teams.
Continuous learning: Evaluates new tools, including AI-assisted ones, with healthy skepticism and adopts them when they add real value.
Why Work for Campbell Scientific?
At Campbell Scientific, you will have the opportunity to work for a company whose technology has a genuine impact on the world. Our instruments and software are used across scientific research, environmental monitoring, climate, renewable energy, infrastructure and many other applications where accurate data matters.
You will join a collaborative, technically focused organisation where innovation, continuous learning and sharing expertise are encouraged. As part of our UK team, you will have the opportunity to work with colleagues and technology teams internationally, giving you exposure to a wide range of projects, technologies and challenges.
We believe in giving our people the opportunity to develop their skills, take ownership of their work and make a meaningful contribution. Whether you are passionate about cloud technology, Kubernetes, automation, cybersecurity, software engineering or the opportunities presented by AI, Campbell Scientific provides an environment where you can develop your expertise while working on technology that makes a difference.