Transform Technical Documentation with AI Expertise
We are seeking a skilled GenAI Engineer to lead our efforts in leveraging Artificial Intelligence to revolutionize how our engineers interact with technical documentation, tools, and processes.
This role involves collaborating with cross-functional teams and external partners to consult on domain expertise and apply advanced AI techniques to real-world challenges.
The successful candidate will directly contribute to enhancing process quality, reducing costs, and boosting efficiency while supporting our mission to innovate and lead in the energy sector.
* Design and implement document processing pipelines to structure complex technical documentation for efficient retrieval.
* Develop and optimize Retrieval-Augmented Generation (RAG) systems for accurate information synthesis from large-scale repositories.
* Architect and deploy multi-agent AI workflows using frameworks such as LangGraph, CrewAI, or AutoGen.
* Create evaluation frameworks to assess and enhance the accuracy of multi-agent AI systems.
* Implement guardrails and validation mechanisms to ensure outputs meet engineering standards and governance requirements.
* Drive continuous improvement through prompt engineering, fine-tuning, and experimentation with agent orchestration patterns.
Successful candidates must possess an academic background in computer science, machine learning, or related fields, along with proven experience in agentic workflow frameworks, unstructured data processing, and RAG architectures.
Familiarity with Python is essential, along with the ability to debug and optimize complex AI systems.
A strong understanding of prompt engineering, few-shot learning, and techniques to improve model outputs is necessary.
Excellent problem-solving, analytical, communication skills, and an agile mindset for managing multiple projects are also essential.