Lead AWS DevOps Engineer

SoftServe; Town of Poland (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

SoftServe is seeking an experienced MLOps Platform Engineer to operate and evolve a cloud-native, multi-tenant MLOps platform. You will work with engineering, data science, and infrastructure teams to ensure security, scalability, reliability, and cost efficiency.

You will manage Terraform-based infrastructure, implement GitOps workflows with ArgoCD and GitHub Actions, and optimize monitoring with Prometheus, Grafana, CloudWatch, and Datadog.

Qualifications

• Experience building and operating a Kubernetes-based MLOps platform.
• Proficient with Terraform, Terragrunt and Helm for IaC and deployment.
• Experience with GitOps and CI/CD tools (ArgoCD, GitHub Actions).
• Strong knowledge of AWS services (EKS, IAM, VPC, Route53, S3, ECR).
• Experience with monitoring and observability (Prometheus, Grafana, CloudWatch, Datadog).
• Proficient in Python and Bash scripting.

Responsibilities

• Operate, maintain, and improve a Kubernetes-based MLOps platform.
• Manage infrastructure using Terraform and GitOps practices.
• Support tenant onboarding, platform services, deployment pipelines, and ML workflows.
• Monitor platform health, respond to incidents, and improve operational processes.
• Optimize platform performance, reliability, security, and cloud costs.
• Collaborate with engineering, data science, and infrastructure teams to deliver a stable and scalable platform.

Skills

Kubernetes

AWS (EKS, IAM, VPC, Route53, S3, ECR)

Terraform

Terragrunt

Helm

GitOps

ArgoCD

GitHub Actions

Prometheus

Grafana

CloudWatch

Datadog

Python

Bash

Security best practices

Communication

Collaboration

NVIDIA GPU tech (nice to have)

Tools

AWS

Kubernetes

Terraform

Terragrunt

Helm

ArgoCD

GitHub Actions

Prometheus

Grafana

CloudWatch

Datadog

Python

Bash

GPU infrastructure

Job description

About The Role

In this role, you will be responsible for operating and evolving a cloud‑native, multi‑tenant MLOps platform that supports machine learning and data science workloads. You will work closely with engineering, infrastructure, and data teams to ensure the platform remains secure, scalable, reliable, and continuously improving. Your work will directly contribute to enabling efficient AI/ML development and production environments across the organization.

Responsibilities

• Operate, maintain, and improve a Kubernetes-based MLOps platform
• Manage infrastructure using Terraform and GitOps practices
• Support tenant onboarding, platform services, deployment pipelines, and ML workflows
• Monitor platform health, respond to incidents, and improve operational processes
• Optimize platform performance, reliability, security, and cloud costs
• Collaborate with engineering, data science, and infrastructure teams to deliver a stable and scalable platform

Requirements

• Experience with AWS services, including EKS, IAM, VPC, Route53, S3, ECR, and related cloud infrastructure
• Strong Kubernetes administration skills, including cluster operations, networking, autoscaling, and troubleshooting
• Hands‑on experience with Infrastructure as Code using Terraform, Terragrunt, and Helm
• Experience with GitOps and CI/CD tools such as ArgoCD and GitHub Actions
• Knowledge of identity and access management, observability, and platform security best practices
• Experience with monitoring tools such as Prometheus, Grafana, CloudWatch, or Datadog
• Scripting and automation skills using Python and/or Bash
• Strong problem‑solving skills and experience supporting production environments
• Excellent communication and collaboration skills
• Experience with NVIDIA technologies, including GPU infrastructure, GPU operators, CUDA, or AI/ML platform optimization (nice to have)

SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.