Website:
m37labs.com
Job details:
Job Summary
We seek an experienced Senior DevOps Engineer to lead cloud infrastructure, CI/CD strategies, and deployment automation for our AI/ML workloads. You'll architect scalable systems, mentor juniors, and drive operational excellence in a collaborative, fast-paced environment focused on enterprise AI innovation.
Key Responsibilities
- Design and optimize CI/CD pipelines using Jenkins, GitLab CI, ArgoCD, or equivalent for complex AI model deployments.
- Architect and manage multi-cloud infrastructure (AWS, Azure, GCP) with Kubernetes, Docker, and IaC tools like Terraform and Pulumi.
- Implement advanced monitoring, logging, and observability with Prometheus, Grafana, ELK stack, and chaos engineering practices.
- Lead security hardening, compliance audits (ISO 27001/42001), and zero-trust architectures for production AI systems.
- Automate workflows with Python/Bash/Go scripting and integrate with Jira, Confluence for agile DevOps practices.
- Mentor junior engineers, conduct code reviews, and drive on-call optimizations while scaling for high-availability AI services.
- Collaborate with R&D, data science, and sales teams to enable rapid AI prototyping to production.
Requirements
- Bachelor's/Master's in Computer Science, IT, or equivalent with 3+ years in DevOps/SRE roles.
- Proven expertise in container orchestration (Kubernetes EKS/AKS/GKE), cloud-native services, and IaC.
- Strong experience with CI/CD, GitOps, and monitoring tools in production-scale environments.
- Proficiency in Linux, networking, security best practices, and scripting for automation.
- Familiarity with AI/ML ops (e.g., Kubeflow, MLflow, SageMaker) and agile tools like Jira.
- Excellent stakeholder communication skills; UK English proficiency preferred.
Preferred Skills
- Leadership in MLOps pipelines for enterprise AI deployments.
- Certifications: AWS/GCP Solutions Architect, CKA/CKAD, Terraform Associate.
- Experience with edge AI, serverless, or multi-region high-availability setups.
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