· Research and develop innovative LLM, Generative AI, and Agentic AI solutions for chemical and process industry applications
· Design and build AI-powered applications that leverage plant data, engineering knowledge, maintenance records, and operational documentation to improve decision making
· Develop and deploy Retrieval-Augmented Generation (RAG) systems, knowledge graphs, and semantic search solutions to enable contextualized engineering insights
· Build and orchestrate intelligent agents capable of interacting with enterprise systems, industrial databases, digital twins, and engineering tools to automate workflows and support operations
· Develop scalable, reliable, and secure AI solutions, ensuring effective deployment, monitoring, maintenance, and continuous improvement in production environments
· Apply machine learning, deep learning, multimodal AI, and advanced analytics techniques to solve challenges related to predictive maintenance, anomaly detection, process optimization, and asset performance
· Build data engineering pipelines for acquiring, cleaning, enriching, and contextualizing structured and unstructured industrial data
· Collaborate with researchers, software engineers, process engineers, and business stakeholders globally to design, evaluate, and deliver AI solutions from concept through production deployment
· Automate engineering and business processes using AI, APIs, scripting, and open-source technologies to improve efficiency, scalability, and knowledge management
· Stay current with advancements in LLMs, Agentic AI, machine learning, industrial AI, and emerging technologies, continuously contributing new ideas and innovations to the organization