About Chryselys

Chryselys is a Excellent Place to Work Certified Pharma Analytics & Business consulting company that delivers data-driven insights leveraging AI-powered, cloud-native platforms to achieve high-impact transformations. We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights.

Role Summary

Design, build and operate the Python/FastAPI services that extract entities and relationships from unstructured documents, resolve them to canonical identifiers, maintain the knowledge graph, and serve graph-augmented retrieval alongside vector search for multi-hop and relational questions.

Responsibilities
- Build entity and relation extraction services over unstructured documents — molecules, brands, indications, therapeutic areas, endpoints, claims.
- Build entity resolution: alias handling, blocking and candidate generation, fuzzy and embedding matching, calibrated thresholds, human review routing.
- Design and maintain the graph schema and ontology; incremental ingest, node and edge deduplication and merging,



provenance on every edge.
- Fuse graph and vector results into a single ranked, cited context for the retrieval service.
- Instrument, monitor and support the services in production.

Qualifications
- 5–9 years software engineering, with demonstrable knowledge-graph construction and applied NLP delivered to production.
- Has built a knowledge graph from unstructured text — not queried an existing one, and not a CRUD application on a graph database.
- Graph at production scale.
Millions of nodes and edges; incremental updates with stable node identity; supernode and traversal-explosion handling with bounded depth and timeouts.
- Entity resolution at corpus scale.
Blocking and candidate generation that avoid O(n²) comparison, with measured precision on a labelled sample.
- Graph database in production.
Neo4j, Amazon Neptune or equivalent; Cypher / openCypher fluency.
- Ontology and taxonomy mode

📌 Graph RAG (Hyderabad)
🏢 Proof-of-Skill
📍 Hyderabad