Job Title: AI/ML DevOps Engineer (AWS) – Infrastructure Lifecycle Management (ILM)

Client: JPMC

Location: Plano, TX - Onsite

12+ years

Position Overview

JPMorgan Chase 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 LangChain.
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.
Thanks & Regards

Shyam (SAM)

Sr.Recruiter

Email: sam.s@navasoftware.com

NAVA Software Solutions

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