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
