Senior DevOps Engineer
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Key skills for this role
About the Role
The employer is looking for a Senior DevOps Engineer to build and run infrastructure for Generative AI products, including CI/CD, container platforms, and AI workload support. The role requires 8+ years of DevOps experience, strong AWS and Terraform skills, and hands-on experience with AI/ML workloads in production.
Key Skills for This Role
Responsibilities
- Write and maintain infrastructure as code for reproducible environments
- Own CI/CD pipelines for building, testing, scanning, and deploying applications and model serving services
- Run the container platform (EKS, ECS, or Fargate) and deployment workflows including GitOps
- Stand up runtime for AI workloads: GPU capacity, model serving, inference autoscaling, and gateways
- Manage API gateways, networking, load balancing, DNS, and certificates
- Own secrets, identity, and least privilege access across environments
- Run databases in production: clustering, replication, failover, backups, and recovery
- Build monitoring including token usage and GPU utilization with alerting and service objectives
- Lead reliability and security practice: incident response, policy as code, vulnerability scanning, and cost discipline
Requirements
- Eight or more years in DevOps, SRE, or infrastructure engineering
- Hands on experience supporting AI or ML workloads in production
- Strong infrastructure as code with Terraform or OpenTofu
- Configuration management with Ansible
- Solid AWS experience across compute, networking, IAM, and storage
- Strong CI/CD with GitHub Actions
- Containers and orchestration: Docker with Kubernetes (EKS preferred), Helm, and ECR
- API gateway experience with Kong or Amazon API Gateway
- Database operations including clustering and high availability with RDS/Aurora, PostgreSQL, and Redis/ElastiCache
- Secrets management with HashiCorp Vault, AWS Secrets Manager, or Parameter Store
- Observability with Prometheus, Grafana, CloudWatch, and OpenTelemetry
- Comfort in Linux and scripting with Bash and Python
Full Job Posting
Role Overview
- This role builds and runs the infrastructure our Generative AI products depend on: the pipelines that ship code, the platforms that run services and models, and the controls that keep all of it secure and reliable.
- AI workloads bring their own demands. GPUs, model serving, inference autoscaling, and token cost all shape the work, and you have run workloads like these before.
- You should be comfortable owning infrastructure as code, CI/CD, observability, and security on AWS, and ready to set the operational standards a growing team will lean on.
What You Will Do
- Write and maintain infrastructure as code so environments are reproducible, reviewable, and quick to recover
- Own CI/CD: the pipelines that build, test, scan, and deploy applications, agents, and model serving services
- Run the container platform (EKS, ECS, or Fargate) and the deployment workflows on top of it, including GitOps where it fits
- Stand up the runtime for AI workloads: GPU capacity, model serving such as vLLM, Triton, or TGI, inference autoscaling, and the gateways and caching that sit in front of the models
- Manage API gateways, networking, load balancing, DNS, and certificates so services are exposed safely and predictably
- Own secrets, identity, and least privilege access across every environment
- Run databases in production: clustering, replication, failover, backups, and recovery
- Build monitoring into everything, including token usage and GPU utilisation, with alerting and clear service objectives
- Lead reliability and security practice: incident response, policy as code, vulnerability and container scanning, and cost discipline, which matters once GPUs are in the mix
Requirements
- Eight or more years in DevOps, SRE, or infrastructure engineering overall. That includes hands on experience supporting AI or ML workloads in production, which can be a more recent part of your background.
- Strong infrastructure as code with Terraform or OpenTofu, including module design and remote state. Experience with HCP Terraform (formerly Terraform Cloud) is a plus
- Configuration management with Ansible
- Solid AWS experience across compute, networking (VPC, subnets, security groups, load balancers, Route 53), IAM, and storage
- Strong CI/CD with GitHub Actions, including reusable workflows and careful handling of credentials
- Containers and orchestration: Docker with Kubernetes (EKS preferred), Helm, and a registry such as ECR
- API gateway experience with Kong or Amazon API Gateway, including auth, rate limiting, and routing
- Database operations including clustering and high availability, with RDS or Aurora, PostgreSQL, and a cache such as Redis or ElastiCache
- Secrets management with HashiCorp Vault, AWS Secrets Manager, or Parameter Store
- Observability with Prometheus, Grafana, CloudWatch, and OpenTelemetry, or close equivalents
- Comfort in Linux and scripting with Bash and Python
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