{"id":4013706,"url":"https://alion.io/job/dotmatics-devops-engineer-luma","title":"DevOps Engineer | Luma","company":{"id":3788,"name":"Dotmatics","domain":"dotmatics.com","url":"https://alion.io/company/dotmatics","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ireland"],"countries":["IE"],"hiring_countries":["IE"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Bash","optional":false},{"name":"Checkov","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CloudFormation","optional":false},{"name":"Copilot","optional":false},{"name":"Datadog","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"GraphPad Prism","optional":false},{"name":"IAM","optional":false},{"name":"ISO 27001","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kyverno","optional":false},{"name":"Least Privilege","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Loki","optional":false},{"name":"MySQL","optional":false},{"name":"Octopus Deploy","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Snyk","optional":false},{"name":"SOC 2","optional":false},{"name":"SonarQube","optional":false},{"name":"TeamCity","optional":false},{"name":"Terraform","optional":false},{"name":"Trivy","optional":false},{"name":"Vault","optional":false}],"status":"live","first_seen_at":"2026-11-10T10:44:22Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-10T11:33:57Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Our Why At Dotmatics \nAt Dotmatics, a Siemens company, we believe science, data, and decision-making must be deeply intertwined for innovation to thrive. Our Portfolio includes Luma, LumaLab Connect, ELN Platform, Graphpad Prism, Geneious, SnapGene, Protein Metrics, OMIQ, FCS Express, LabArchives, NQuery, EasyPanel, SoftGenetics and Virscidian.\nWe have a vision for a new Lab of the Future that will change the future of scientific research.\nWe have created the world’s most comprehensive digital science platform - best-of-breed software applications already used by more than 2 million scientists, together in a single ecosystem united by a powerful, flexible enterprise data platform. This is not flat data buried away in digital graveyards. This is dynamic, multi-dimensional decision-making.\nScientific enterprises need a new level of effectiveness to achieve tomorrow’s breakthroughs. Illness will not wait. The biosphere will not wait. We are tireless in our vision, because the time for innovation is now.\nShaping the Future of Science At Dotmatics \nOur global team of more than 800 colleagues are dedicated to supporting our customers in over 180 countries. Together, with our scientific community of users, we accelerate scientific innovation in order to make the world a healthier, cleaner, and safer place to live.\nYou’ll join a collaborative, global team pushing the boundaries of scientific innovation. Your ideas and efforts will have a tangible impact, accelerating scientific progress and discovery. We offer a dynamic, remote-friendly environment that fosters high integrity and collaboration, empowering you to excel. Dotmatics is a company built by scientists, for scientists. Combined, we are now the world’s largest cloud-based scientific research R&D platform. We need your help to keep growing and pioneering the future.\nWe are Science Driven. We are Customer Centric. We are Better Together. \nWhat do we need\nDotmatics is seeking a DevOps Engineer to join our team working on ground-breaking Scientific Software products such as Luma. In this role, you will have the opportunity to apply your knowledge to help improve our processes, infrastructure and security by applying best practices with the latest technologies. You will be AI fluent and know how AI influences engineering and DevOps \nIn this role you will get to:\nDesign and manage CI/CD and deployment pipelines for both AWS-native and Kubernetes-based applications\nProvide advice/assistance to the product teams, clarifying requirements for deployment\nCollaborate with product teams on cloud and container best practices\nManage IT infrastructure in cloud computing environments\nAutomation: Use CI tools to automate code changes, builds, testing, and analysis\nMonitoring: Monitor performance after release\nDevelop and improve monitoring systems for automated alerts\nStrategy: Design and manage the DevOps infrastructure, pipelines, and processes\nSECURITY: Embed security into every stage of the delivery lifecycle (DevSecOps), including automated SAST, DAST, dependency, secrets, and container image scanning in CI/CD pipelines\nSECURITY: Implement and enforce least-privilege IAM, network segmentation, encryption in transit and at rest, and secrets management (e.g. AWS Secrets Manager, Vault, KMS)\nSECURITY: Harden Kubernetes clusters and cloud environments using policy-as-code, admission controls, runtime protection, and CIS/NIST benchmarks\nSECURITY: Support vulnerability management, incident response, audit readiness, and compliance efforts (e.g. SOC 2, ISO 27001)\nAI: Use AI-assisted tooling to accelerate pipeline development, infrastructure code, troubleshooting, and incident analysis\nAI: Apply AI/ML-driven capabilities to monitoring, including anomaly detection, alert noise reduction, and automated root-cause analysis\nAI: Build and operate deployment pipelines and infrastructure for AI/ML and LLM-based workloads, including model serving, GPU-enabled clusters, and cost controls\nAI: Establish guardrails for responsible AI use in engineering workflows, including data privacy, access controls, and review of AI-generated code and configuration\nWe are looking for people who have 8+ years of experience maintaining high-traffic applications and complex technical infrastructure. You will be someone with a proven background in supporting cloud environments, with hands-on experience translating AWS Well-Architected principles into action.\nThe key skills we are looking for:\nKubernetes clusters/customer cloud environments\nAWS (ECS, EKS, ALB, EC2, S3, RDS, CloudFront, Route53, etc.)\nInfrastructure-as-code (Terraform, CloudFormation, Pulumi)\nCI/CD tools (Octopus Deploy, GitHub Actions, Jenkins, TeamCity, CodePipeline, etc.)\nAPMs and logging (e.g. Datadog, Grafana, Prometheus, Loki, ELK, App Insights)\nNetworking concepts in cloud environments\nSoftware development lifecycle processes/version control\nSecurity: DevSecOps practices, AWS security services (IAM, GuardDuty, Security Hub, WAF, Config, KMS), container and supply chain security (image signing, SBOMs), and security scanning tools (e.g. Trivy, Snyk, SonarQube, Checkov)\nSecurity: Familiarity with Kubernetes security (RBAC, network policies, Pod Security Standards, OPA/Kyverno) and secrets management\nAI: Practical experience using AI coding and operations assistants (e.g. GitHub Copilot, Claude, Amazon Q) to improve engineering productivity\nAI: Understanding of how to deploy and operate AI/ML workloads (e.g. Amazon Bedrock, SageMaker, model-serving on Kubernetes) and observe their performance and cost\nAI: Awareness of AI-specific risks such as prompt injection, data leakage, and insecure AI-generated code\nYou may also have:\nScripting languages (e.g. Python, Bash)\nLinux administration and networking (e.g. HTTP/2)\nMicroservice and serverless architectures\nExperience with GitOps tooling (e.g. Argo CD, Flux)\nExperience building internal tooling or agents that apply AI to DevOps workflows (e.g. automated incident triage, ChatOps)\nRelevant certifications (e.g. AWS Certified DevOps Engineer, AWS Security Specialty, CKA/CKS)\nDatabases (e.g. PostgreSQL, MySQL, MongoDB)\nExposure to AI-enabled tooling or workflows, with openness to incorporating AI into day-to-day work\nResearch shows us the confidence gap and imposter syndrome can get in the way of meeting outstanding candidates, so please don’t hesitate to apply - we’d love to hear from you.\nBy submitting your application, you agree that Dotmatics may collect your personal data for recruiting, global organization planning, and related purposes. Dotmatics Privacy Notice explains what personal information we may process, where we may process your personal information, our purposes for processing your personal information, and the rights you can exercise over Dotmatics use of your personal information. \nDotmatics is an equal opportunity employer. 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