AI DevOps/ AI/ML Engineer
Posted Updated
Summary
Senior (7+ yrs) DevSecOps/SRE engineer focused on AI/ML: builds and automates secure CI/CD pipelines for AI systems — LLMs (Claude/OpenAI), agentic frameworks (LangChain, LangGraph, CrewAI), RAG, vector DBs, MCP — using Python and cloud platforms (AWS/Azure/GCP) with tools like Jenkins, GitLab, SonarQube, Artifactory. Hybrid in Charlotte, NC or Iselin, NJ.
AI DevOps/ AI/ML Engineer needs 7+ years of experience in DevSecOps, Site Reliability Engineering,
AI DevOps/ AI/ML Engineer requires:
- 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
- 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 (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
- Bachelor's degree in Computer Science, Engineering, or related field
- Hybrid
AI DevOps/ AI/ML Engineer duties:
- 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