About the Role
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.
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.
Qualifications
- 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.
- Nice to have: understanding of vector databases, knowledge graphs, and retrieval-augmented generation.
- Nice to have: familiarity with Azure or AWS development environments.
- Azure AI Engineer or Azure Data Engineer certification is a plus; AWS experience is nice to have, but not required.
- Oil and gas domain experience is a strong advantage, especially familiarity with digital operations or engineering workflows; candidates with relevant AI system-building experience in other complex industries are encouraged to apply.
- Minimum qualifications may be acquired through technical schools or equivalent related experience. Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.
Benefits
- Leadership and competency development, competitive compensation plans, health benefits, work-life programs, and reward and incentive plans.
Certifications
Azure AI Engineer / Azure Data Engineer certification (a plus)
Skills
Architect
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