Dotmatics

Cloud-based R&D informatics for life sciences

DevOps Engineer - Luma

DevOps EngineeringPosted on Nov 13

Full-timeRemote in Ireland$79.7k - $107.8kRemote

About the Job

Requirements

At least 8 years of experience maintaining high-traffic applications and complex technical infrastructure.
A proven background supporting cloud environments and hands-on experience applying AWS Well-Architected principles.
Experience with Kubernetes clusters and customer cloud environments.
Experience with AWS services such as ECS, EKS, ALB, EC2, S3, RDS, CloudFront, and Route53.
Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Pulumi.
Experience with CI/CD tools such as Octopus Deploy, GitHub Actions, Jenkins, TeamCity, or CodePipeline.
Experience with APM and logging tools such as Datadog, Grafana, Prometheus, Loki, ELK, or App Insights.
Knowledge of networking concepts in cloud environments.
Knowledge of software development lifecycle processes and version control.
Knowledge of DevSecOps practices, AWS security services such as IAM, GuardDuty, Security Hub, WAF, Config, and KMS, container and supply-chain security including image signing and SBOMs, and security scanning tools such as Trivy, Snyk, SonarQube, or Checkov.
Familiarity with Kubernetes security, including RBAC, network policies, Pod Security Standards, OPA or Kyverno, and secrets management.
Practical experience using AI coding and operations assistants such as GitHub Copilot, Claude, or Amazon Q to improve engineering productivity.
Understanding of deploying and operating AI/ML workloads, such as with Amazon Bedrock, SageMaker, or model serving on Kubernetes, and observing their performance and cost.
Awareness of AI-specific risks such as prompt injection, data leakage, and insecure AI-generated code.

Responsibilities

Design and manage CI/CD and deployment pipelines for AWS-native and Kubernetes-based applications.
Advise and assist product teams by clarifying deployment requirements.
Collaborate with product teams on cloud and container best practices.
Manage IT infrastructure in cloud computing environments.
Use CI tools to automate code changes, builds, testing, and analysis.
Monitor performance after releases.
Develop and improve monitoring systems for automated alerts.
Design and manage DevOps infrastructure, pipelines, and processes.
Embed security throughout the delivery lifecycle, including automated SAST, DAST, dependency, secrets, and container-image scanning in CI/CD pipelines.
Implement and enforce least-privilege IAM, network segmentation, encryption in transit and at rest, and secrets management, such as AWS Secrets Manager, Vault, or KMS.
Harden Kubernetes clusters and cloud environments using policy-as-code, admission controls, runtime protection, and CIS or NIST benchmarks.
Support vulnerability management, incident response, audit readiness, and compliance efforts such as SOC 2 or ISO 27001.
Use AI-assisted tooling to accelerate pipeline development, infrastructure code, troubleshooting, and incident analysis.
Apply AI/ML-driven monitoring capabilities, including anomaly detection, alert-noise reduction, and automated root-cause analysis.
Build and operate deployment pipelines and infrastructure for AI/ML and LLM-based workloads, including model serving, GPU-enabled clusters, and cost controls.
Establish responsible-AI guardrails for engineering workflows, including data privacy, access controls, and review of AI-generated code and configuration.

Desired Qualifications

Experience with scripting languages such as Python or Bash.
Linux administration and networking experience, including HTTP/2.
Experience with microservice and serverless architectures.
Experience with GitOps tools such as Argo CD or Flux.
Experience building internal tooling or agents applying AI to DevOps workflows, such as automated incident triage or ChatOps.
Relevant certifications such as AWS Certified DevOps Engineer, AWS Security Specialty, or CKA/CKS.
Experience with databases such as PostgreSQL, MySQL, or MongoDB.
Exposure to AI-enabled tooling or workflows and openness to incorporating AI into day-to-day work.

Our Why At Dotmatics

At 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.

We have a vision for a new Lab of the Future that will change the future of scientific research.

We 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.

Scientific 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.

Shaping the Future of Science At Dotmatics

Our 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.

You’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.

We are Science Driven. We are Customer Centric. We are Better Together.

What do we need

Dotmatics 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

In this role you will get to:

Design and manage CI/CD and deployment pipelines for both AWS-native and Kubernetes-based applications
Provide advice/assistance to the product teams, clarifying requirements for deployment
Collaborate with product teams on cloud and container best practices
Manage IT infrastructure in cloud computing environments
Automation: Use CI tools to automate code changes, builds, testing, and analysis
Monitoring: Monitor performance after release
Develop and improve monitoring systems for automated alerts
Strategy: Design and manage the DevOps infrastructure, pipelines, and processes
SECURITY: Embed security into every stage of the delivery lifecycle (DevSecOps), including automated SAST, DAST, dependency, secrets, and container image scanning in CI/CD pipelines
SECURITY: Implement and enforce least-privilege IAM, network segmentation, encryption in transit and at rest, and secrets management (e.g. AWS Secrets Manager, Vault, KMS)
SECURITY: Harden Kubernetes clusters and cloud environments using policy-as-code, admission controls, runtime protection, and CIS/NIST benchmarks
SECURITY: Support vulnerability management, incident response, audit readiness, and compliance efforts (e.g. SOC 2, ISO 27001)
AI: Use AI-assisted tooling to accelerate pipeline development, infrastructure code, troubleshooting, and incident analysis
AI: Apply AI/ML-driven capabilities to monitoring, including anomaly detection, alert noise reduction, and automated root-cause analysis
AI: Build and operate deployment pipelines and infrastructure for AI/ML and LLM-based workloads, including model serving, GPU-enabled clusters, and cost controls
AI: Establish guardrails for responsible AI use in engineering workflows, including data privacy, access controls, and review of AI-generated code and configuration

We 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.

The key skills we are looking for:

Kubernetes clusters/customer cloud environments
AWS (ECS, EKS, ALB, EC2, S3, RDS, CloudFront, Route53, etc.)
Infrastructure-as-code (Terraform, CloudFormation, Pulumi)
CI/CD tools (Octopus Deploy, GitHub Actions, Jenkins, TeamCity, CodePipeline, etc.)
APMs and logging (e.g. Datadog, Grafana, Prometheus, Loki, ELK, App Insights)
Networking concepts in cloud environments
Software development lifecycle processes/version control
Security: 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)
Security: Familiarity with Kubernetes security (RBAC, network policies, Pod Security Standards, OPA/Kyverno) and secrets management
AI: Practical experience using AI coding and operations assistants (e.g. GitHub Copilot, Claude, Amazon Q) to improve engineering productivity
AI: 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
AI: Awareness of AI-specific risks such as prompt injection, data leakage, and insecure AI-generated code

You may also have:

Scripting languages (e.g. Python, Bash)
Linux administration and networking (e.g. HTTP/2)
Microservice and serverless architectures
Experience with GitOps tooling (e.g. Argo CD, Flux)
Experience building internal tooling or agents that apply AI to DevOps workflows (e.g. automated incident triage, ChatOps)
Relevant certifications (e.g. AWS Certified DevOps Engineer, AWS Security Specialty, CKA/CKS)
Databases (e.g. PostgreSQL, MySQL, MongoDB)
Exposure to AI-enabled tooling or workflows, with openness to incorporating AI into day-to-day work

Research 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.

By 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.

Dotmatics is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work.

Salary Range [MIN-MAX]: 79650.51 - 107762.46 USD

About the Company

Dotmatics

Cloud-based R&D informatics for life sciences

Dotmatics provides a cloud-based R&D software platform for life sciences, chemistry, biology, and materials research that helps researchers capture, analyze, visualize, and share experimental data. Its suite combines data management, workflow automation, and analytics, with tools like Luma for low-code multimodal drug discovery and applications such as GraphPad Prism, SnapGene, and Geneious. The platform harmonizes diverse scientific data in a single environment to improve collaboration, reduce manual work, and speed up discovery, used by millions of scientists across thousands of organizations. In 2025, Dotmatics was acquired by Siemens and integrated into Siemens Digital Industries Software, expanding Siemens' AI-driven product lifecycle capabilities into life sciences.

Company size: 501-1,000
Company stage: Acquired
Total funding: $106M
Headquarters: Boston, MA
Founded: 2005

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