Senior / Lead Graph RAG & GenAI Engineer
Teamware Solutions
About the role
About the Company
Greetings from Teamware Solutions a division of Quantum Leap Consulting Pvt. Ltd
Teamware Solutions (a division of Quantum Leap Consulting Pvt. Ltd.) is a 20+ year industry leader providing IT staffing and consulting services, supporting 4000+ professionals across India, USA, Middle East, and APAC for leading GCC clients.
About the Role
- Position: Senior / Lead Graph RAG & GenAI Engineer
- Locations: Bangalore, Pune, Gurgaon, Hyderabad
- Work Model: Hybrid (2 days office)
- Experience: 3.6 - 8 Years
- Notice Period: Immediate - 15 days
- Shift timing: General or 2PM to 11PM
- No of Pos: 2
Key Skills
- Data Science, ML, and Knowledge Graph with Neo4j and Agentic AI experience is also required
- Python, AI, Knowledge Graph - must
- Coding must - 2 interview round (If required they will take 3 rounds)
Role Summary
We are seeking a Senior / Lead Knowledge Graph & GenAI Engineer to design, build, and scale large‑scale knowledge graph platforms and Graph RAG systems for reasoning‑heavy GenAI applications. This role requires strong expertise in Neo4j, Cypher, graph data modeling, and Graph‑based RAG frameworks (LangChain, LangGraph), along with hands‑on experience managing terabyte‑scale graph databases in production.
You will work at the intersection of graph databases, LLMs, and distributed systems, enabling high‑impact, AI‑driven knowledge platforms.
Required Skills & Experience
- Strong hands‑on experience with Neo4j (Enterprise preferred).
- Advanced proficiency in Cypher, including indexing, constraints, and query optimization.
- Proven experience managing large, complex, and evolving graph datasets.
- Experience operating TB‑scale databases with performance and reliability constraints.
- Experience with distributed or enterprise graph databases (e.g., InfiniGraph or similar).
- Solid understanding of graph theory, traversal patterns, and graph algorithms.
- Hands‑on experience with LangChain and LangGraph.
- Strong understanding of RAG architectures, especially Graph RAG.
- Experience integrating LLMs with structured data sources; familiarity with embeddings and vector databases.
- Strong Python development skills.
- Experience building REST / GraphQL APIs.
- Familiarity with cloud platforms (Azure, AWS, or GCP) and Docker, Kubernetes, CI/CD.
Application
Please let me know if you are interested in this position and send me your resume to netra.s@twsol.com
Requirements
- Strong hands‑on experience with Neo4j (Enterprise preferred).
- Advanced proficiency in Cypher, including indexing, constraints, and query optimization.
- Proven experience managing large, complex, and evolving graph datasets.
- Experience operating TB‑scale databases with performance and reliability constraints.
- Experience with distributed or enterprise graph databases (e.g., InfiniGraph or similar).
- Solid understanding of graph theory, traversal patterns, and graph algorithms.
- Hands‑on experience with LangChain and LangGraph.
- Strong understanding of RAG architectures, especially Graph RAG.
- Experience integrating LLMs with structured data sources; familiarity with embeddings and vector databases.
- Strong Python development skills.
- Experience building REST / GraphQL APIs.
- Familiarity with cloud platforms (Azure, AWS, or GCP) and Docker, Kubernetes, CI/CD.
Responsibilities
- Design, build, and scale large‑scale knowledge graph platforms and Graph RAG systems for reasoning‑heavy GenAI applications.
Skills
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