DevOps + MLOps Engineer

Luxoft; Dadri, Hyderabad, Gurugram District; On-site; INR 350,000 - 550,000; Full time

Job summary

Luxoft in India (Dadri) seeks an experienced DevOps/Platform Engineer to design and operate scalable cloud infrastructure. The role emphasizes hands-on AWS, Terraform automation, and container platforms.

You will collaborate to enable ML workflows and MLOps practices, ensuring secure, observable systems across multi-account environments with ECS/EKS, Docker, and CI/CD tooling in a regulated setting.

Qualifications

• 8+ years of experience in DevOps, Platform Engineering, or SRE roles.
• Deep hands-on AWS expertise including EC2, EKS/ECS, VPC, IAM, S3, RDS/DynamoDB, CloudWatch, Lambda.
• Strong Terraform experience, modular architectures, multi-account setups.
• Experience rolling out Agentic AI infrastructure with networking, security, and governance.
• Hands-on with AI/ML tooling, CI/CD, and agent-based automation.
• Solid Linux, networking, and cloud security fundamentals.
• Experience with Docker and Kubernetes-based platforms (Docker, EKS).
• Familiarity with MLOps or AI platform components.

Skills

DevOps

Platform Engineering

Site Reliability Engineering

Cloud security fundamentals

Tools

Amazon Bedrock

AWS

Terraform

Docker

Kubernetes

ECS

EKS

MLOps

Job description

Mandatory Skills:

Amazon Bedrock Amazon Elastic Container Service (ECS) AWS HashiCorp Terraform Machine Learning Operations (MLOps)

Mandatory Skills Description:

• 8+ years of experience in DevOps, Platform Engineering, or Site Reliability Engineering roles.
• Deep, hands-on AWS expertise, including services such as:
• EC2, EKS/ECS, VPC, IAM, S3, RDS/DynamoDB, CloudWatch, Lambda
• Strong production experience with Terraform, including:
• Designing modular Terraform architectures
• Managing state, environments, and multi-account setups
• Proven experience rolling out Enterprise-grade Agentic AI infrastructure on top of existing platforms, including:
• Supporting agent execution within established networking, security, and compliance boundaries
• Enabling scalability, observability, and governance for agent behavior
• Hands-on experience supporting agentic SDLC tools and processes, such as:
• AI-assisted coding, testing, and deployment workflows
• Agent-based automation within CI/CD and operational processes
• Solid understanding of Linux, networking, and cloud security fundamentals.
• Experience with containerized and Kubernetes-based platforms (Docker, EKS).
• Familiarity with MLOps or AI platform components (model serving, vector databases, feature stores).