What this role actually asks for
Extracted by RemoteHuntMust have
- •5+ years relational, object, graph, vector databases
- •3+ years Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
- •3+ years schema design, ontology management, KG curation
- •3+ years KG solutions and graph-based ML models
- •2+ years end-to-end data pipeline for AI (LLMs)
- •2+ years leading a team or workstream
- •2+ years cloud platforms (AWS, Azure, GCP)
Nice to have
- •Diverse ML techniques and agentic systems
- •Prompt engineering
Tools and technologies
The full posting
Role As our Knowledge Engineer, you will own the ontology and knowledge graph layer that sits underneath every APAS product. You'll take the regulatory, engineering, and operational knowledge that water utilities and the consulting firms serving them rely on, and structure it into knowledge graphs and semantic models our AI can reason over accurately and consistently. We're at the stage where we're actively building out our integrations layer, so the calls you make on ontology structure, graph store design, and how new data sources map into our existing models will directly shape what gets built next across the company. You won't inherit a finished system to maintain. You'll be defining the foundation, and those decisions need to hold up as we add products and expand into new jurisdictions. This is not a job you'll do in a silo . Expect tight and transparent communication loops across our team. Must Have Minimum 5 years of experience with relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases Minimum 3 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Minimum 3 years of experience in schema design, ontology management, and KG curation Minimum 3 years of designing and developing KG solutions and graph-based ML models (functional + technical) Minimum 2 years of experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration Minimum 2 years of experience in leading a team or workstream within a larger program Minimum 2 years of experience with cloud platforms (AWS, Azure, GCP) Minimum 2 years of experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow) Practical experience with NLP and/or Search technique Prompt engineering, and LLMs for enterprise-scale application Strong expertise in designing and implementing ontologies and semantic models Experience in building and managing knowledge graphs for complex data relationships Ability to apply advanced analytics techniques to extract insights from structured and unstructured data Familiarity with data integration and transformation processes within cloud environments Strong communication skills (verbal and written) Nice to Have Broad experience in diverse ML techniques and agentic systems Location India, Remote Compensation $1,500 - $2,500 per month
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