AI DevOps Engineer

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 and Duties

• Formulates system scope through research and fact-finding to develop or modify moderately complex information systems.
• Evaluates and implements changes to existing system logic difficulties and documentation as necessary.
• Reviews flow charts, models, and procedures and feasibility studies to design possible system solutions.
• Reviews technical documentation to guide system users and to assist with the ongoing operation, maintenance, and development of the system.
• Collaborates with system analysts, engineers, and programmers to design systems and to determine project limitations and capabilities, performance requirements, systems performance standards, and interfaces.
• Identifies and documents all system constraints, implications and consequences of various proposed system changes.
• Educates end users on system designs and functionalities through creation of training materials and conducting demos.
• Evaluates the efficiency and effectiveness of application operations and troubleshooting problems.

• 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