AI Research Engineer – Knowledge Graphs & Multi-Agent Systems

Required Skills & Experience

• Master's degree with 2+ years of relevant experience OR PhD in Computer Science, Electrical Engineering, Mathematics, AI, Knowledge Representation, Reasoning, or related field
• Expertise building Knowledge Graphs from structured and unstructured data
• Experience integrating graph-based reasoning with Generative AI
• Proven experience designing and deploying multi-agent workflows
• Hands-on experience with graph databases such as Neo4j, Amazon Neptune, or equivalent
• Advanced Python development skills, including writing, debugging, and maintaining production-quality code
• Willingness to travel at least 2 weeks per year

Nice to Have Skills & Experience

• Experience working with multimodal data (text, imagery, time-series data, code repositories)
• Knowledge of cyber-physical systems
• Understanding of industrial control systems (ICS)
• Strong technical communication and presentation skills
• Experience leading or contributing to advanced research initiatives
• Background in industrial AI, energy, or infrastructure environments

Job Description

Insight Global is seeking an AI Research Engineer – Knowledge Graphs & Multi-Agent Systems for a leading energy technology and research organization. This candidate will help advance next-generation AI capabilities by developing knowledge graph solutions, graph-based reasoning systems, and multi-agent architectures that support complex decision-making across industrial environments. The ideal candidate will have deep expertise in knowledge representation, generative AI, graph databases, and Python development. This role offers the opportunity to work on cutting-edge research initiatives, transforming advanced AI concepts into real-world solutions for critical energy and cyber-physical systems while collaborating with multidisciplinary teams of researchers and engineers.

Day-to-Day:

• Design and implement Knowledge Graph pipelines using industrial structured and unstructured data
• Develop AI architectures that combine graph reasoning and generative AI capabilities
• Build and orchestrate multi-agent systems for complex decision-making workflows
• Architect and manage graph database environments
• Develop scalable, reusable, research-grade Python applications
• Extract and synthesize information from heterogeneous data sources
• Collaborate with cross-functional research and engineering teams
• Transform advanced research concepts into industrial prototypes and production-ready solutions
• Support AI-driven insights and reasoning for energy and cyber-physical systems