AI Systems Developer

We are seeking an innovative AI Engineer to join our team and play a key role in the development of cutting-edge artificial intelligence solutions for the power sector.

The ideal candidate will have hands-on experience with LLMs, RAG, and agentic architectures, as well as solid Python programming skills and expertise in modern AI/ML libraries.

You will be responsible for designing, building, and deploying AI-powered systems that integrate advanced generative AI and LLM technologies.

Additionally, you will work on fine-tuning and prompt-engineering LLMs for task-specific reasoning, planning, and dynamic adaptation, as well as developing and deploying agentic AI systems capable of autonomous decision-making and multi-agent collaboration.

Responsibilities:

• Conduct research and development on specific AI problems critical to power system operations, leveraging OATI's vast datasets spanning decades.
• 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.
• Design, build, and fine-tune large foundation AI models (e.g., LLMs, multimodal models) for the energy domain.
• 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.

Education:

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field; PhD preferred.

Technical Skills:

• 3+ years building and deploying AI-powered systems using LLMs, RAG, and agentic architectures.
• Solid Python programming skills and experience with modern AI/ML libraries.
• Advanced knowledge of LLMs, including fine-tuning, prompt engineering, and evaluation.
• Proven experience implementing RAG systems and integrating vector databases or external knowledge stores.
• Proven experience in building and fine-tuning foundation models (e.g., LLMs, vision transformers, multimodal models) for different domains (such as energy, healthcare, finance, etc.).
• Past experience in implementing association rule mining algorithms to uncover patterns and relationships within large and diverse datasets.
• Past experience in building similarity search pipelines using vector representations to enable accurate ranking and retrieval based on multidimensional feature similarity.
• Deep knowledge of agentic AI frameworks and multi-agent system design.
• Proven ability to design and implement multi-agent systems and agent-to-agent communication.
• Strong background in neural network architectures, including transformers and other models.
• Strong background in advanced mathematics and statistics for model optimization and validation.
• Familiarity of Model Context Protocol and best practices for managing AI model context and state.
• Proficiency in Python and relevant AI/ML frameworks such as TensorFlow or PyTorch.
• Excellent problem-solving skills and ability to communicate complex AI concepts to technical and non-technical stakeholders.
• Strong foundation in machine learning concepts, including algorithms (e.g., deep learning, reinforcement learning) and statistical methods.
• Experience with AI system security, compliance, and ethical AI considerations.
• Knowledge of natural language processing (NLP) pipelines and data engineering.
• Familiarity with conversational AI and chat bot frameworks.
• Familiarity with version control systems like Git.
• Familiarity with SQL and No-SQL database engines is a plus.

Gain valuable experience working on real-world AI projects with a significant impact on the future of power systems.

Work alongside leading experts in AI and the energy sector.

Potential for co-authorship on research publications (depending on contribution).

Opportunity to develop your research skills and expertise in a rapidly evolving field.

Be part of a dynamic and collaborative research team working on a critical global challenge.

Excellent analytical and problem-solving skills with the ability to tackle complex problems.

Strong communication skills to present research findings and collaborate effectively within a team.

Ability to work independently and manage time effectively.

A passion for research and development in the field of AI and a strong interest in the power sector.