Job 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.
Key Responsibilities
- 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.
Required Skills And Experience
- Demonstrated expertise in building Agentic AI architectures, using frameworks like LangChain, AutoGen, 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 toolchains across complex systems.
- Comfortable operating independently with minimal supervision in a cross-functional environment.
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.
