Use Case

Description

Knowledge Graph Q&A

Build graph-powered chatbots using LLMs + Cypher retrieval

Entity Resolution

Link entities across data sources using graph relationships

Recommendation Engine

Graph traversal-based recommendations enriched with semantic search

Document Intelligence

Extract entities from unstructured text and load into Neo4j

 

• Design, build, and maintain Knowledge Graphs in Neo4j, defining node labels, relationship types, and ontologies for complex domains.
• Develop GraphRAG pipelines, combining graph traversal with LLM-based generation for intelligent question-answering and search.
• Write optimized Cypher queries for data retrieval, pattern matching, and graph analytics.
• Build and manage data ingestion pipelines from structured and unstructured sources into Neo4j using Python.
• Integrate vector databases alongside Neo4j for hybrid semantic + graph search.

• GenAI & LLMs

• Experience with LLM frameworks — LangChain, LlamaIndex, or similar — for building RAG applications.
• Understanding of embedding models, vector search, and semantic similarity.
• Prompt engineering and chaining experience for structured outputs.

• Programming & Data Engineering

• Proficient in Python — data pipelines, API integrations, and scripting.
• Experience with data pipeline tools (Airflow, Prefect, or similar).
• Comfortable with REST APIs and working with JSON/CSV/structured datasets.

• Good to Have

• Cloud experience — AWS (Bedrock, SageMaker) or Azure (OpenAI Service).
• Knowledge of graph analytics — Neo4j GDS library (PageRank, community detection, pathfinding).
• Exposure to streaming platforms like Kafka or Spark for real-time graph ingestion.
• Familiarity with GraphQL or Spring Data Neo4j for application integration.
• Experience with visualization tools — Neo4j Bloom, Gephi, or Linkurious.

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• 3+ years of experience in data engineering, with a focus on graph databases and machine learning.
• Proficiency in Neo4j and Cypher, with a strong understanding of graph data modeling.
• Experience with Python for data ingestion and pipeline development.
• Knowledge of vector databases (Pinecone, Weaviate, FAISS) and their integration with graph databases.

• Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 3–5 years of hands-on experience in data engineering, software development, or AI/ML roles.
• At least 1–2 years of direct experience with Neo4j or other graph databases (ArangoDB, Amazon Neptune).
• Neo4j Certified Professional certification is a strong plus.

At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.