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AI DevOps​/AI​/ML Engineer

Job in Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listing for: Globalchannelmanagement
Full Time position
Listed on 2026-02-16
Job specializations:
  • IT/Tech
    AI Engineer, Cloud Computing, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: AI DevOps/ AI/ML Engineer

AI Dev Ops/ AI/ML Engineer needs 7+ years of experience in Dev Sec Ops , Site Reliability Engineering,

  • LLM ( Claude/ OpenAI) with focus on reasoning/agentic use cases
  • Agentic AI framework Lang Chain, Lang Graph, CrewAI
  • MCP
  • RAG
  • Python language proficiency is must.
  • Deep understanding of cloud engineering as related AI, Dev Ops, 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
  • Iselin, NJ, Charlotte, NC
  • 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 (Tensor Flow, PyTorch, scikit-learn)
  • Experience with CI/CD tools (Jenkins, Git Hub, Git Lab 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
  • Bachelor's degree in Computer Science, Engineering, or related field
  • Hybrid
  • Implement version control for code, data, and models using Git Lab, Sonar Qube, Jenkins, Artifactory
  • Automate testing frameworks using AI capabilities, including model validation tests
  • Automated build, scans and deploy including vulnerability remediation capabilities
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