AI Agent Architect; on-site

Project description

We are seeking a hands-on and qualified AI Agent Architect to design and deploy advanced Agentic AI systems—comprising task-specific autonomous tools governed by a master agent—to support complex technical decision-making in industrial environments. This is a high-impact individual contributor role for someone who can independently deliver full-stack intelligent agents that interpret natural language queries and generate precise, context-aware outputs by interacting with structured and unstructured data, APIs, and analytical engines.

• Architect and develop a multi-agent AI framework where autonomous agents coordinate to solve domain-specific technical queries.
• Leverage LLMs, NLP, and tool-based reasoning to automate data extraction, analysis, and insight generation.
• Build agents capable of integrating with engineering tools, simulators, databases, and knowledge sources.
• Collaborate with domain experts to align agent behavior with technical expectations and constraints.
• Implement safeguards to ensure accuracy, traceability, and reliability of AI-generated outputs.
• Continuously optimize prompting, agent orchestration, and performance under real-world conditions.
• Business trip to Kuwait for first 6-12 months. On-site

Must have

• Demonstrated expertise in building Agentic AI architectures, using frameworks like Lang Chain, Auto Gen, CrewAI, or custom stacks.
• Strong foundation in LLM-based NLP, prompt engineering, and context-aware reasoning.
• Advanced Python programming and experience deploying AI workflows in cloud or containerized environments.
• Ability to work with APIs, data models, and external tool chains across complex systems.
• Comfortable operating independently with minimal supervision in a cross-functional environment.
• Ready for a long term business trip to Kuwait for first 6-12 months

Nice to have

• Exposure to industrial domains such as energy, manufacturing, or heavy engineering.
• Understanding of vector databases, knowledge graphs, and retrieval-augmented generation.
• Familiarity with Azure or AWS development environments.
• Certifications:
  
  Azure AI Engineer or Azure Data Engineer certification is a plus.
• AWS experience is nice to have, but not required.
• Industry
  
  Experience:
  
  Oil and gas domain experience is a strong advantage, especially familiarity with digital operations or engineering workflows.
• However, candidates with relevant AI system-building experience in other complex industries are encouraged to apply.