knowledge graph developper at Pattern Agentix · Remote only · 2 - 7 years · ₹6L - ₹12L / yr · Raised funding · Remote only · Posted 26 Jun 2025
Pattern Agentix is seeking a skilled engineer to design and develop a comprehensive knowledge graph that spans multiple biological domains—including molecular biology, biochemistry, biophysics, immunology, virology, pharmacology, and computational biology. The goal is to integrate heterogeneous datasets (ontologies, public databases, scientific literature) into a scalable, semantically rich graph that supports hypothesis generation and interdisciplinary research.
Responsibilities:
• Architecture & Design:
- Develop a scalable knowledge graph architecture using graph databases
- Design data models to capture entities (e.g., genes, proteins, chemical compounds, immune markers) and their relationships.
• Data Integration & Curation:
- Integrate data from domain-specific ontologies (e.g., Gene Ontology, ChEBI) and public repositories (e.g., UniProt, PDB).
- Build API connectors and automation pipelines for data ingestion.
- Leverage NLP tools to extract relationships from scientific literature with validation by domain experts.
• Collaboration & Documentation:
- Work closely with interdisciplinary teams and domain experts to ensure semantic accuracy.
- Document data models, integration methods, and curation guidelines.
Requirements:
• Proven experience in knowledge graph development and graph databases
• Strong programming skills (Python, Java, or similar) and experience with API development.
• Familiarity with semantic web technologies (RDF, ) and ontology management tools
• Solid background in bioinformatics, computational biology, or related disciplines.
• Demonstrated ability to work with heterogeneous data sources and interdisciplinary projects.
Contract
We are seeking part time or full time on contract and will compensate to local norms.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Pattern Agentix
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- Build ontology-driven systems using frameworks such as LinkML, OWL, SHACL, or similar schema modeling tools, and implement knowledge representations using RDF triples or labeled property graphs.
- Design and optimize entity resolution algorithms using techniques such as blocking strategies, embedding similarity, and rule-based matching.
- Develop ontology alignment techniques and graph embedding models such as Node2Vec or TransE-style approaches where appropriate.
- Design hybrid retrieval architectures combining dense vector retrieval, sparse retrieval techniques, and graph traversal algorithms such as BFS, DFS, path ranking, and neighborhood expansion.
- Build validation systems that enforce schema conformance, detect semantic inconsistencies, and reduce hallucinated or invalid structured outputs.
- Integrate structured knowledge systems into GraphRAG pipelines, agent planning frameworks, and tool-selection workflows.
- Deliver production-grade semantic systems with clear targets for latency, scalability, reliability, and data integrity.
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- 5+ years of experience building production AI or machine learning systems.
- Strong experience designing and implementing knowledge graphs or ontology-driven architectures.
- Hands-on experience implementing structured extraction techniques, including grammar-constrained decoding, JSON schema enforcement, or AST-style parsing approaches.
- Experience building entity resolution systems beyond simple embedding similarity methods.
- Experience working with graph query languages such as SPARQL or Cypher and optimizing graph query performance.
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- Experience designing compositional semantic extraction pipelines.
- Experience implementing reasoning engines or rule-based inference systems.
- Experience benchmarking and evaluating structural extraction accuracy and consistency.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
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Location: Banglore / Hyderabad
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We are looking for a Senior/Lead Full Stack Engineer – Gen AI / Agentic AI with strong hands-on experience in Python, React.js, MongoDB, Java/Spring Boot and Generative AI/Agentic AI.
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- MCP / AI Agent orchestration
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- Docker / Kubernetes
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- CI/CD – Jenkins / GitHub Actions
- LLMOps / AI evaluation / observability
- ELK / Grafana / Splunk / AppDynamics
- SQL / NoSQL
- Agile/Scrum
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon