• Design, build, and maintain Azure infrastructure using Terraform across dev, staging, and production environments • Own and improve Azure DevOps CI/CD pipelines (YAML), including artefact management, approvals, and automated deployments • Implement and maintain secure Azure networking (VNets, subnets, Private Endpoints, Private DNS, NSGs) to ensure private access to critical services • Configure and enforce security best practices across the platform (RBAC, Managed Identities, Service Principals, Key Vault, secrets handling) • Ensure reliable hosting and operations for platform components (App Service, Functions, Storage, Azure SQL, ACR) • Monitor platform health and performance; troubleshoot incidents using Azure monitoring, logs, and diagnostics • Support the AI processing infrastructure needs, including enabling secure and scalable execution for workflows and batch/experimental pipelines (and optionally Azure ML / Azure OpenAI)

Role Description You will be: - designing and implementing scalable AWS infrastructure across multi-account environments, - building and maintaining reusable Infrastructure as Code (Terraform) modules and platform components, - implementing automation across provisioning, deployment, and governance workflows, - embedding security, compliance, and operational controls into CI/CD pipelines using policy-as-code, - improving platform reliability through observability, monitoring, and incident response practices, - collaborating with platform, security, and application teams to deliver and adopt platform capabilities. Qualifications - 8+ years of experience in cloud, infrastructure, or platform engineering roles, - strong hands-on experience designing and operating AWS environments at scale (multi-account), - proven expertise in Infrastructure as Code such as Terraform, - experience implementing CI/CD pipelines and embedding DevSecOps practices, - strong knowledge of AWS core domains - networking, IAM, container platforms (e.g. EKS), and security principles, - experience improving platform reliability through observability, monitoring, and incident management, - familiarity with least-privilege IAM strategies, and secure-by-design cloud architecture, - practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. Requirements - Work from the European Union region and a work permit are required. Benefits - AWS certifications (e.g. Solutions Architect – Professional, DevOps Engineer – Professional) are nice to have, - experience implementing AWS landing zones and Control Tower at scale, - familiarity with policy-as-code and automated compliance controls, - experience working in large-scale, distributed enterprise environments, - exposure to FinOps practices and cloud cost optimization strategies, - experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work, - interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. Recruitment Process - CV review - HR call - Interview - Client Interview - Decision

• Design and implement a Golden Path CI/CD pipeline using GitHub Actions and GitOps principles • Standardize and optimize CI/CD processes across engineering teams • Build and maintain scalable deployment workflows using ArgoCD and Helm • Collaborate with development teams to improve developer experience and release efficiency • Ensure reliability, scalability, and maintainability of CI/CD infrastructure • Contribute to best practices around infrastructure automation and delivery pipelines • Work within a complex Kubernetes environment (50+ clusters), ensuring consistency and performance at scale

Role Description We are looking for a Senior DevOps / Infrastructure Engineer to join our existing DevOps team. This is a senior IC role with a broad technical scope: - Own complex initiatives end-to-end. - Drive collaboration across engineering and science teams. - Set a high bar for how we build and operate infrastructure. - Support R&D teams by running and evolving compute clusters that power bioinformatics pipelines, ML training, and other HPC workloads. Highly autonomous: able to operate with minimal guidance, prioritize work independently, and take full ownership of infrastructure decisions and outcomes. Qualifications - 10+ years of infrastructure and DevOps engineering experience, with a proven track record in senior or lead IC roles. - Ability to take end-to-end ownership of complex, multi-team initiatives and drive them from design through to production. - Hands-on experience running HPC or research compute clusters: bare-metal provisioning, Slurm (or equivalent), GPU infrastructure, and shared storage (NFS, Lustre, or similar). - Comfortable operating in environments with a mix of cloud, VPS, and bare-metal systems, including legacy or non-standard setups. - Experience supporting scientific or R&D teams with mixed workloads: long-running CPU batch jobs, GPU training jobs, and interactive compute. - Deep, hands-on AWS expertise: EKS/Kubernetes, IAM, VPC networking, S3, RDS, and cost management. - Solid Terraform skills and a principled approach to infrastructure-as-code. - Strong Linux fundamentals and experience managing multi-node environments at scale. - Experience owning and improving production observability systems (Prometheus/Grafana, OpenTelemetry, ELK, or similar). - Strong security fundamentals: threat modeling, least-privilege access design, vulnerability management, and compliance frameworks. - Experience owning incident management end-to-end, including process design and continuous improvement. - Excellent communication skills; able to work directly with researchers and scientists as well as with engineering and leadership. - Fluent English. Requirements - Background in biotech, bioinformatics, or scientific computing environments (Nice-to-Have). - SOC 2 Type II audit experience (Nice-to-Have). - Monorepo tooling and developer platform engineering (Nice-to-Have). Key Responsibilities - Own our cloud infrastructure across AWS and third-party hosting and compute providers; ensure it is reliable, scalable, and cost-efficient. - Own and operate bare-metal compute clusters: node provisioning, configuration management, networking, secure access, and ongoing reliability. - Build and maintain configuration management using Ansible (or similar), ensuring reproducible and scalable server provisioning. - Set up and maintain Slurm for job scheduling across CPU and GPU node pools; ensure researchers can submit, monitor, and manage jobs without DevOps involvement. - Design and manage cluster networking: management and storage networks, inter-node communication, DNS, and secure perimeter access, including bastion/jump host setup. - Deep hands-on experience managing Linux-based infrastructure, including networking, firewalls, VPNs, and performance tuning in distributed environments. - Own disaster recovery and business continuity: define RTO/RPO targets, maintain runbooks, and run regular tests. - Manage and optimize infrastructure spend through capacity planning, right-sizing, and intelligent use of reserved and spot capacity. - Manage Kubernetes clusters, networking, and workload scheduling across cloud and on-premise environments. - Enable infrastructure-as-code practices in Terraform; drive consistency, modularity, and auditability across the codebase. - Evolve our observability platform: improve coverage, reduce alert noise, and ensure engineering teams have the visibility they need to detect and resolve issues quickly. - Own security posture across the platform: IAM policies, secrets management, network segmentation, vulnerability management, and SOC 2 compliance. - Lead incident management: on-call processes, escalation policies, runbooks, and blameless post-mortems. - Drive CI/CD improvements and developer workflow initiatives that meaningfully increase engineering throughput. - Evolve internal tooling and CLI infrastructure that engineering teams depend on daily. Values & Working Style - Ownership mindset — you take responsibility from A to Z. - Comfortable navigating ambiguity in a fast-moving startup environment. - Clear communicator who can collaborate across technical and non-technical teams. - Pragmatic problem solver focused on impact. Why This Role Matters Now As we scale our AI platform and expand into new initiatives, engineering velocity and platform reliability directly impact research outcomes and product milestones. This role plays a key part in strengthening our technical foundation during the growth phase.