DevOps Engineer

Responsibilities

• Support and maintain scalable, highly available, secure cloud infrastructure.
• Provision and manage cloud resources with Terraform, Terragrunt, and CloudFormation.
• Implement cloud security controls, IAM, encryption, vulnerability management, and secure infrastructure configurations.
• Maintain containerized environments, orchestration platforms, CI/CD pipelines, and zero-downtime deployment strategies.
• Automate configuration management, infrastructure provisioning, deployments, and operational processes.
• Design, deploy, operate, and secure infrastructure for AI and agentic products.
• Operate and scale Databricks clusters, jobs compute, ML pipelines, and model-serving endpoints.
• Manage production model-serving capacity, throughput, autoscaling, monitoring, and serving health.
• Maintain monitoring, logging, metrics, alerting, and observability systems.
• Support incident response, root-cause analysis, deployment troubleshooting, and disaster recovery activities.
• Partner with Software Engineering, ML Engineering, QA, Security, IT, and Product Support teams.
• Maintain technical and operational documentation and provide infrastructure support.

Requirements

• At least 3 years of experience in DevOps, Cloud Engineering, Site Reliability Engineering, or a similar infrastructure-focused role.
• At least 2 years of hands-on experience with AWS services including EC2, S3, RDS, Lambda, IAM, VPC, SQS, and API Gateway, or similar services.
• At least 2 years of experience with containerized environments and orchestration platforms such as Kubernetes and Amazon EKS.
• Strong experience building and maintaining CI/CD pipelines with GitLab CI/CD or Jenkins.
• Hands-on Infrastructure as Code experience with Terraform, Terragrunt, CloudFormation, or similar technologies.
• Strong Linux system administration, troubleshooting, networking, routing, load balancing, and network security skills.
• Scripting experience with Python, Bash, or similar languages.
• Hands-on experience using AI tools for engineering workflows, automation, troubleshooting, or agentic use cases.
• Experience supporting data, ML, or compute-intensive production workloads.
• Google Cloud and multi-cloud experience are valuable.
• Familiarity with Helm and service mesh technologies such as Istio, Linkerd, or Traefik is beneficial.
• Experience with serverless and event-driven architectures, cloud security, vulnerability management, observability, FinOps, API management, and MLOps is preferred.
• Knowledge of security standards, compliance requirements, cloud security practices, Databricks, model serving, ML pipelines, and model monitoring is beneficial.

Benefits

• Flexible work model combining in-person and remote work.
• 15 days of vacation, floating holidays, company holidays, wellness benefits, and paid parental leave.
• Comprehensive medical, dental, vision, life, and disability insurance.
• 401(k) plan.
• Work-from-home stipend for home office setup.
• Learning platform, training, and onboarding support.