AI Engineer

OATI • Full-time • Bloomington, MN, US • $100k - $150k / year • 1d ago

Open Access Technology International (OATI) is seeking highly motivated individuals to join our team of AI Engineers focused on power systems. This is a fantastic opportunity to gain practical experience working on real-world AI applications alongside leading experts in the energy sector. The starting salary for this role ranges from $100k - $150k per year, commensurate with experience. Our team is tackling critical challenges in electric power system operations using Artificial Intelligence. Responsibilities: Conduct research and development on specific AI problems critical to power system operations, leveraging OATI's vast datasets spanning decades (e.g., forecasting load, wholesale electricity market prices, renewable energy generation; optimizing grid reliability, resiliency, and stability; signature analysis and anomaly detection). Design, build, and deploy agentic AI systems using frameworks such as LangChain, LangGraph and related agentic libraries. Implement and optimize retrieval-augmented generation (RAG) pipelines ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses. Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning and dynamic adaptation. Lead the development of enterprise-grade AI platform that integrates advanced generative AI and LLM technologies. Develop and deploy agentic AI systems capable of autonomous decision-making and multi-agent collaboration. Build and optimize neural network models tailored to use cases in the energy/power systems industry ensuring high performance and scalability. Implement and standardize Model Context Protocol based communication to ensure consistent context management across AI models and agents. Establish and enforce best practices for MLOps, model monitoring and observability to ensure robust, scalable and maintainable AI solutions Develop and implement machine learning models using popular frameworks (e.g., TensorFlow, PyTorch) to analyze and extract meaningful insights from power system data. Participate in the full research cycle, including literature review, data exploration, experimentation, analysis and presentation of findings. Collaborate effectively with other researchers, engineers and data scientists. Contribute to the development and documentation of technical code.

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