Manager Note: Candidates did not have a lot of app development experience. Submittals seem to be more of devops integrator with a little app dev knowledge. Looking more on dev side vs the infrastructure. Someone who has implemented AI modules and is very hands-on.
Overview
An AI 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, Google Cloud Platform)
• 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.
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