Job Requirements

Build and maintain production Python (or Go) services that read from and write to Postgres and the graph store.

Design and implement REST APIs consumed by AI agents and product teams.

Own performance and correctness of graph and relational query paths — query optimization, execution-plan analysis, materialized-view strategy.

Own the API contract for internal and external consumers — versioning, deprecation, and consumer communication.

Own end-to-end reliability of ingestion: idempotency, retries, duplicate handling, partial failure, and replay.

Set technical direction for the Data & Knowledge Services layer — modeling decisions for claims, entities, and qualifiers; storage architecture; API strategy.

Mentor P2 and P3 engineers on modeling, query engineering, and production practices.

A production service (an API surface or an ingestion pipeline) end-to-end, including its SLOs, observability, incident response, and evolution over time.

The technical architecture of the Data & Knowledge Services layer — modeling decisions, storage choices, and how the system evolves as scale grows and consumer needs shift.

Intermediate to advanced SQL and relational database design.





REST API development in Python or Go (or the team's backend stack).

Genuine appetite to learn graph modeling and Cypher (or equivalent)

Advanced Postgres SQL — indexing, execution plans (EXPLAIN ANALYZE), and zero-downtime schema migration.

Cypher or an equivalent graph query language, with hands-on query performance tuning.

REST or GraphQL API development for non-trivial systems.

Integration testing across multiple stores (Postgres + graph).

Distributed systems literacy: idempotency, retries, duplicate event handling, partial failure, replay.

Observability practice: reading dashboards, tracing latency, and diagnosing production issues without a script.

Data modeling for relationship-heavy domains — including qualifiers, reification, and n-ary relations — with real production experience.

Expert-level Postgres and a graph database (Neo4j, Neptune, JanusGraph, or RDF/SPARQL) operated in production.

API architecture for AI-agent and human consumers at scale, including rate limiting, query complexity control, and multi-tenant fairness.

System design for data-intensive services with real cost, latency, and reliability tradeoffs.

Work Experience

10-15Years

📌 Architect (Pune)
🏢 Virtusa
📍 Pune