Lead Engineer - Neuro Symbolic AI

Job Title: Lead Engineer - Neuro Symbolic AI & Agentic SystemsLocation: Remote (India)Employment Type: Full-timeMust Have skills:- Cypher Query, Neo 4J, Neuro Symbolic AI, LangGraph, LangChain, Knowledge Graph

Job SummaryWe are seeking a Lead Engineer - Neuro Symbolic AI & Agentic Systems to design, develop, and deploy enterprise scale intelligent systems that fuse Generative AI, autonomous agents, symbolic reasoning, and Knowledge Graphs.The ideal candidate will bring strong expertise in Python, LLM based systems, agentic frameworks, and knowledge centric AI, with hands on experience delivering production grade GenAI or agentic solutions grounded using Knowledge Graphs (Neo4j).you will lead the architecture and implementation of agentic, reasoning driven AI platforms, mentor engineers, shape technical strategy, and enable scalable AI solutions across multiple enterprise domains.

Key ResponsibilitiesLead the design and implementation of agentic AI systems using frameworks such as LangGraph, AutoGen, LangChain, or similar.Architect neuro symbolic AI solutions that integrate: Large Language Models (LLMs)Symbolic reasoning, rules, and constraintsKnowledge Graphs for grounding and explainabilityDesign and implement Knowledge Graphs using Neo4j for: LLM grounding and hallucination mitigationAgent memory, planning, and reasoningExplainable multi hop inferenceDevelop and optimize Cypher queries, graph schemas, and indexing strategies in Neo4j.Implement Graph RAG and hybrid retrieval pipelines combining vector databases and Knowledge Graphs.Architect and deploy scalable APIs (REST/WebSocket) for AI and agent workflows.Deploy and maintain multiple GenAI / Agentic AI solutions in production, ensuring reliability, scalability, and security.Integrate SQL, No SQL, vector, and graph databases (Postgres, MongoDB, Neo4j, ChromaDB, etc.).Provide technical leadership and mentorship to AI and platform engineers.Collaborate with cross functional teams to deliver AI solutions across banking, insurance, and healthcare domains.Ensure governance, compliance, observability, and robustness of AI systems.Stay current with advancements in Generative AI, agentic systems, symbolic reasoning, and knowledge centric AI.Document system designs and present solutions to both technical and non technical stakeholders.

Required QualificationsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or related field.7+ years of overall professional experience in AI/ML, Data Science, or advanced software engineering.5+ years of strong hands on experience in Python, with solid software engineering best practices.3+ years of experience building Generative AI or Agentic AI systems, including production deployments.Hands on experience with LLMs, prompt engineering, and model integration.Practical experience with Knowledge Graph design and implementation.Strong experience working with: Neo4j and CypherSQL, No SQL, vector databasesProven experience deploying production grade AI systems with scalability and reliability considerations.Solid understanding of data pipelines, ETL, and data modeling.

Preferred QualificationsExperience with LangGraph, AutoGen, LangChain, or similar agent orchestration frameworks.Experience designing multi agent systems and long horizon reasoning workflows.Knowledge of neuro symbolic AI concepts, logic based reasoning, or rule based systems.Experience with Graph Data Science (GDS) or graph based inference techniques.Familiarity with MLOps practices (CI/CD, monitoring, experimentation, retraining).Experience working in regulated or enterprise environments.Contributions to open source projects, internal AI platforms, or applied AI research.Strong problem solving skills and ability to thrive in fast paced R&D environments.