While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role: Knowledge Graph Engineer
Experience Level: 5 to 7 Years
Work location: Mumbai/Bangalore/Trivandrum
RESPONSIBILITIES
● Implement graph schemas including entity types, relationship types, property definitions, and provenance attributes against client-provided specifications.
● Design and implement concept linking logic connecting entities across graph boundaries with full provenance tracking.
● Manage schema versioning and schema evolution without requiring full re-ingestion.
● Build idempotent batch ETL pipelines ingesting structured data from FHIR APIs, ontology datasets, and metadata sources into a graph database at scale.
● Write and optimise graph queries (Cypher, SPARQL, or Gremlin) for production access patterns: entity lookup, multi-hop traversal, hierarchy navigation, and lineage queries.
● Tune query performance to meet latency and concurrency targets as the graph scales to tens of millions of records.
● Expose graph access patterns as MCP tools for consumption by LLM-based orchestration agents.
● Define and execute retrieval quality benchmarks: precision, recall, traversal accuracy, latency against test query sets and produce validation reports.
● Author operational runbooks, schema versioning procedures, and handoff documentation
MUST-HAVE REQUIREMENTS
Minimum 5 years overall experience with at least 3 years in production knowledge graph or graph database engineering.
Knowledge Graph Engineering:
Production-grade experience building knowledge graphs: entity modelling,
relationship typing, provenance attributes, and schema versioning in a live
operational system with concurrent users and continuous data updates.
Graph Database Platforms
Hands-on experience deploying and operating at least one graph DB
platform in production: Neo4j, Amazon Neptune, TigerGraph, Google
Spanner Graph, Cosmos DB (Gremlin API), Stardog, or equivalent. Able to
configure, tune, and troubleshoot under load.
Graph Query Languages
Proficient in at least one of Cypher, SPARQL, or Gremlin. Able to write and
optimise queries for production latency targets and design access patterns
for multi-hop traversals at scale.
Ingestion Pipelines
Able to build production batch and streaming data pipelines end-to-end. Experience with at least one streaming framework (Kafka, Pub/Sub,
Kinesis) and one processing or orchestration tool (Airflow, Apache Beam /
Dataflow, Spark).
API Development
Experience designing and building versioned REST APIs for graph data
exposure with typed schemas, access control, audit logging, and API
gateway integration.
Cloud Platforms
Hands-on with GCP or Azure: IAM, secrets management, managed service
deployment, networking, and Terraform for infrastructure-as-code.
Regulated Data Environments
Experience with sensitive or regulated data (PHI, PII, or equivalent) where
access control, audit logging, and compliance reviews are standard
practice. Healthcare, life sciences, pharma, or financial services
backgrounds are all relevant.
Programming
Production-grade Python for pipeline development and data transformation.
Maintainable, testable code with proper error handling.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Skills Required
- Minimum 5 years overall experience with at least 3 years in production knowledge graph or graph database engineering
- Production-grade knowledge graph engineering: entity modelling, relationship typing, provenance attributes, and schema versioning in live systems
- Hands-on experience deploying and operating at least one graph DB in production (Neo4j, Amazon Neptune, TigerGraph, Spanner Graph, Cosmos DB Gremlin API, Stardog)
- Proficiency in at least one graph query language: Cypher, SPARQL, or Gremlin
- Ability to write and optimize graph queries to meet production latency and concurrency targets
- Experience building idempotent batch and streaming ingestion pipelines; familiarity with Kafka, Pub/Sub, Kinesis and orchestration/processing tools (Airflow, Apache Beam/Dataflow, Spark)
- Experience designing and building versioned REST APIs with typed schemas, access control, audit logging, and API gateway integration
- Hands-on experience with GCP or Azure including IAM, secrets management, managed services, networking, and Terraform
- Experience working in regulated/sensitive data environments (PHI, PII) with access control, audit logging, and compliance reviews
- Production-grade Python for pipeline development and data transformation with maintainable, testable code and error handling
- Experience tuning query performance and scaling graphs to tens of millions of records
- Experience with schema versioning and evolution without full re-ingestion, provenance tracking, and authoring operational runbooks
Quantiphi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Quantiphi and has not been reviewed or approved by Quantiphi.
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Flexible Benefits — Hybrid and work-from-home options are commonly available and perceived as meaningful perks that increase overall package value. Flexibility by team and role often enhances day-to-day experience even when cash pay is not top-tier.
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Healthcare Strength — U.S. materials indicate medical coverage that includes dental and vision, and employee accounts align with having these plans in place. The presence of core health benefits contributes to a baseline of security across key locations.
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Parental & Family Support — Paid parental leave is available in the U.S., with examples citing generous leave lengths. Family-focused policies appear alongside other flexibility features.
Quantiphi Insights
What We Do
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business. Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.
