
AI Research Engineer – Knowledge Graphs & Multi-Agent Systems
Niskayuna, NYJobSeen 4 days agoSeen in employer's feed 4 days ago
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Job overview
Insight Global seeks an AI Research Engineer to develop knowledge graph solutions, graph-based reasoning systems, and multi-agent architectures for industrial decision-making. The role transforms AI research into prototypes and production-ready solutions for energy and cyber-physical systems, working with multidisciplinary research and engineering teams. Candidates need expertise in knowledge representation, generative AI, graph databases, and Python, along with a qualifying graduate degree and experience.
Skills & qualifications
Skills
Qualifications
Full job description
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
Skills and Requirements
- 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
- 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
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to [email protected].
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