DevOps Engineer

Job not on LinkedIn

🔥 1 minute ago

🇬🇧 United Kingdom – Remote

💵 £79.7k - £107.8k / year

⏰ Full Time

🟠 Senior

🔴 Lead

⛑ DevOps & Site Reliability Engineer (SRE)

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Dotmatics

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Dotmatics is an AI-powered scientific intelligence platform that specializes in data management and workflow automation specifically for multimodal scientific discovery. It facilitates adaptive lab workflows, enhances collaboration across various scientific disciplines, and integrates advanced predictive analytics to accelerate research and development. With a suite of products, including solutions for bioinformatics, cheminformatics, and flow cytometry, Dotmatics supports researchers in making informed decisions, streamlining operations, and driving innovation in drug discovery and materials science.

📋 Description

• 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 • Automate code changes, builds, testing, and analysis using CI tools • Monitor application performance after release • Develop and improve monitoring systems for automated alerts • Design and manage DevOps infrastructure, pipelines, and processes • Embed DevSecOps security throughout the delivery lifecycle, including automated SAST, DAST, dependency, secrets, and container image scanning • Implement least-privilege IAM, network segmentation, encryption, and secrets management • Harden Kubernetes clusters and cloud environments using policy-as-code, admission controls, runtime protection, and CIS/NIST benchmarks • Support vulnerability management, incident response, audit readiness, and compliance efforts • Use AI-assisted tooling for pipeline development, infrastructure code, troubleshooting, and incident analysis • Apply AI/ML-driven monitoring capabilities such as anomaly detection, alert noise reduction, and automated root-cause analysis • Build and operate deployment pipelines and infrastructure for AI/ML and LLM workloads, including model serving and GPU-enabled clusters • Establish responsible AI guardrails covering data privacy, access controls, and review of AI-generated code and configuration

🎯 Requirements

• 8+ years of experience maintaining high-traffic applications and complex technical infrastructure • Proven background supporting cloud environments • Hands-on experience translating AWS Well-Architected principles into action • Experience with Kubernetes clusters/customer cloud environments • Experience with AWS services including 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 cloud networking concepts • Knowledge of software development lifecycle processes and version control • Knowledge of DevSecOps practices, AWS security services, container and supply chain security, and security scanning tools • Familiarity with Kubernetes security and secrets management • Practical experience using AI coding and operations assistants such as GitHub Copilot, Claude, or Amazon Q • Understanding of deploying and operating AI/ML workloads and observing their performance and cost • Awareness of AI-specific risks including prompt injection, data leakage, and insecure AI-generated code

🏖️ Benefits

• Dynamic, remote-friendly environment • Collaborative global team • Equal opportunity employer • Welcoming and supportive workplace

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