DevOps - AWS GenAI Engineer - 7+ years

Years of Experience: 8

Job Description: We are seeking an experienced DevOps Engineer to support our AWS Generative AI initiatives, focusing on building secure, scalable, and automated cloud environments. The ideal candidate will be highly proficient in Terraform-based infrastructure automation, Azure DevOps CI/CD pipelines, and AWS AI/ML services, with strong emphasis on security, compliance, and operational excellence. This role will be pivotal in enabling our Data & AI teams to deploy, manage, and operate generative AI workloads efficiently and securely.

Primary Skills: AWS, Sagemaker, Azure DevOps, Terraform, CI / CD Pipeline Build

Secondary Skills: Linux, Docker Containers, Kubernetes

Role Description:

We are seeking an experienced DevOps Engineer to support our AWS Generative AI initiatives, focusing on building secure, scalable, and automated cloud environments. The ideal candidate will be highly proficient in Terraform-based infrastructure automation, Azure DevOps CI/CD pipelines, and AWS AI/ML services, with strong emphasis on security, compliance, and operational excellence.

This role will be pivotal in enabling our Data & AI teams to deploy, manage, and operate generative AI workloads efficiently and securely.

Role Responsibility:

Design, implement, and manage infrastructure-as-code (IaC) using Terraform for multi-account AWS environments.

Build and maintain Azure DevOps CI/CD pipelines for infrastructure and application deployments.

Automate provisioning and configuration of AWS AI/ML services (e.g., SageMaker, Bedrock, Comprehend, Textract, Rekognition, and LLM endpoints).

Establish and enforce security, compliance, and governance controls (IAM, VPC isolation, encryption, TLS, logging, tagging, and cost governance).

Integrate observability tools for monitoring, alerting, and logging across GenAI workloads.

Collaborate with AI/ML, Data Engineering, and Security teams to streamline model deployment workflows and ensure platform reliability.

Maintain environment consistency across Dev, QA, and Prod using automated provisioning and configuration management.

Role Requirement:

5+ years of DevOps / Cloud Engineering experience with a focus on AWS.

Deep hands-on expertise in Terraform (modules, remote states, backends, policy-as-code).

Strong experience in Azure DevOps pipelines (YAML templates, multi-stage deployments, approvals, artifacts).

Solid knowledge of AWS core services (EC2, ECS/EKS, Lambda, RDS, S3, CloudWatch, IAM, CloudTrail).

Familiarity with AWS AI and ML services (SageMaker, Bedrock, Translate, Comprehend, Lex, etc.).

Strong understanding of cloud security best practices — IAM roles, KMS, VPC, endpoint protection,

private connectivity, and encryption.

Proficiency with Linux, networking, and scripting (Python/Bash) for automation tasks.

Strong collaboration and communication skills — ability to work with cross-functional data and AI teams.

Additional Requirement:

Experience with ML model deployment pipelines.

Exposure to Generative AI frameworks and LLM operationalization (RAG, vector stores, fine-tuning).

AWS Certifications (DevOps Engineer Professional, Solutions Architect, or Machine Learning Specialty).