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