Fulltime Role - AI/ML DevOps Engineer (AWS)

Location: Plano, TX (5 Days Onsite) Duration: Contract-to-Hire (CTH) Position: AI/ML DevOps Engineer (AWS) Experience: 7+ Years

Position Overview

Our client is seeking a highly skilled AI/ML DevOps Engineer to join the Infrastructure Lifecycle Management (ILM) and Cloud Operations team. This role will focus on building and supporting AI-powered operational capabilities, agentic AI solutions, DevOps automation, and cloud infrastructure platforms that support enterprise-scale application deployment and lifecycle management.

The ideal candidate will have strong AWS and DevOps expertise combined with hands-on experience implementing AI/ML-driven automation, custom AI agents, and cloud-native infrastructure solutions. This individual will collaborate with application teams, platform engineering teams, and infrastructure operations teams to optimize deployment pipelines, automate operational workflows, and enhance platform reliability.

Key Responsibilities

• Design, develop, and implement AI-powered operational solutions within Infrastructure Lifecycle Management (ILM).
• Build and maintain agentic AI solutions to automate infrastructure provisioning, validation, deployment, and operational workflows.
• Develop custom AI agents leveraging LLM platforms such as Claude, GitHub Copilot, and enterprise AI frameworks like Specate (internal to client)
• Integrate AI agents into DevOps pipelines to improve operational efficiency and reduce manual intervention.
• Design and maintain AWS-based cloud infrastructure supporting enterprise applications.
• Automate infrastructure provisioning using Terraform and Infrastructure as Code (IaC) methodologies.
• Support CI/CD pipeline development for Java or Python-based applications.
• Collaborate with multiple business application teams across horizontal and vertical engineering organizations.
• Develop intelligent validation agents for deployment and infrastructure compliance checks.
• Build automation solutions for infrastructure lifecycle management, cloud operations, and service engineering.
• Evaluate and mitigate AI model hallucination risks through testing, monitoring, and governance practices.
• Participate in architecture reviews and AI solution design discussions.
• Support multi-region deployment strategies and cloud-native operational excellence initiatives.

Required Qualifications

• 7+ years of experience in DevOps, Cloud Engineering, or Platform Engineering.
• 2+ years of hands-on experience with AI/ML, Generative AI, or Agentic AI implementations.
• Strong AWS cloud expertise including: EC2, ECS/EKS, Lambda, IAM, VPC, CloudWatch, S3
• Experience with Infrastructure as Code using Terraform.
• Strong experience with CI/CD tools and pipeline automation.
• Experience deploying and supporting Java and Python applications.
• Experience with containerization technologies: Docker, Kubernetes/EKS
• Experience working with databases: Aurora PostgreSQL, DynamoDB
• Understanding of AI agent development and orchestration frameworks.
• Experience integrating AI capabilities into enterprise operational workflows.
• Strong scripting skills in Python.

Preferred Qualifications

• Experience with Lang Chain.
• Experience with enterprise AI governance frameworks.
• Knowledge of vector databases and Retrieval-Augmented Generation (RAG).
• Experience developing AI agents for infrastructure automation.
• Familiarity with platform engineering and service engineering models.
• Experience supporting enterprise-scale cloud transformation initiatives.