AI DevOps Engineer - Iselin , N

Job Description

Title: AI DevOps Engineer

Location: Iselin , NJ (Hybrid)

Duration: 2 year contract

Overview

An AI DevOps Engineer bridges the gap between artificial intelligence development and operations, ensuring that AI models and systems are deployed efficiently, monitored effectively, and maintained reliably in production environments.

Key Responsibilities

AI/ML Engineer

• Implement version control for code, data, and models using GitLab, SonarQube, Jenkins, Artifactory
• Automate testing frameworks using AI capabilities, including model validation tests
• Design blue/green deployment strategies using AI capabilities
• Automated build, scans and deploy including vulnerability remediation capabilities

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field
• 7+ years of experience in DevSecOps, Site Reliability Engineering,
• Hands on knowledge of AI tools, Models, practical use case implementation
• Proficiency in at least one programming language commonly used in AI (Python, Java)
• Hands-on experience with cloud platforms (AWS, Azure, GCP)
• Understanding of ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Experience with CI/CD tools (Jenkins, GitHub, GitLab CI, Artifactory)
• Hands on experience with automated security vulnerability detection and remediation using security scanning tools in DAST/SAST/IAST scanning space
• Hands on experience building and deploying Agentic capabilities using AI Agentic tools, processes across the technology and business landscape

Skills

• LLM ( Claude/ OpenAI) with focus on reasoning/agentic use cases

• Agentic AI framework LangChain, LangGraph, CrewAI
• Context Engineering
  • MCP
  • Vector databases
  • RAG
• Python language proficiency is must.
• Deep understanding of cloud engineering as related AI, DevOps, Automation
• Strong troubleshooting and problem-solving abilities
• Excellent communication skills to work with both data scientists and operations teams
• Familiarity with agile development methodologies
• Knowledge of security best practices for AI systems
• Ability to balance technical requirements with business needs