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Senior DevOps Engineer
Location
United Kingdom
Posted
142 days ago
Salary
0
Seniority
Senior
Job Description
Senior DevOps Engineer
Brahma
• Own build, deploy, and runtime reliability across BRAHMA AI’s hybrid estate. • Deliver secure, scalable infrastructure for Gen AI based workflows and products across hybrid environments. • Partner with infrastructure and multidisciplinary product and research teams to help them innovate and ship fast. • Design, implement, and operate Slurm and Kubernetes-based platforms across cloud and on-prem GPU nodes, including autoscaling, rollout strategies, and multi-cluster operations. • Build CI/CD pipelines for services, model training, and model serving; standardise artifact/version management and environment promotion. • Implement Infrastructure as Code with Terraform/Terragrunt and configuration management; enforce drift detection and repeatable environments. • Design and implement observability stacks (metrics, logs, tracing); drive incident response and postmortems. • Secure the stack with least privilege, secrets management, network policy, and hardened baselines; support ISO/MPA controls with the security team. • Operate model-serving infrastructure for real-time and batch workloads; optimise GPU utilisation, concurrency, and latency. • Drive cost visibility and efficiency across compute, storage, and egress; forecast capacity and plan lifecycle of hardware and licenses.
Job Requirements
- 6+ years in DevOps/SRE/Platform roles running production systems.
- Expert with Kubernetes and containers (runtime, scheduling, networking, autoscaling).
- Strong with Terraform and at least one configuration management tool (Ansible preferred).
- CI/CD (GitHub Actions [preferred] / GitLab), release strategies, and artifact registries.
- Observability in production (Prometheus/Grafana preferred).
- Linux mastery, shell scripting, and a high-level language (Python preferred).
- Cloud proficiency (AWS/GCP/Azure) and Security fundamentals: IAM, secrets management, network segmentation, image provenance.
- Experience with data-/media-heavy workloads or ML pipelines in production.
Benefits
- Professional development opportunities
- Flexible working arrangements
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