Project Role : Knowledge Engineer
Project Role Description : Design and structure knowledge frameworks that enable AI systems to reason and make informed decisions. Capture and translate expert and unstructured knowledge into ontologies knowledge graphs and semantic models ensuring accuracy and context for automation and insights. Apply advanced analytics on knowledge graphs to drive problem-solving and actionable insights.
Must have skills : Neo4j
Good to have skills : Snowflake Data Warehouse
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary / Description
AI Powered Tech Talent
Engineer role in Knowledge Engineering for a strong individual contributor who helps build scalable Knowledge Graph semantic layer ontology and AI-enabled data solutions using Snowflake Data Cloud capabilities. The role works hands-on across the knowledge graph lifecycle from ingestion through modeling curation implementation integration and deployment. The role applies current methodologies generative AI LLM multimodal graph search and semantic techniques to practical business problems while collaborating with users use case representatives engineers architects UI designers and delivery teams. The role must include industry experience or project exposure in domains such as banking insurance healthcare retail telecom manufacturing energy public sector or life sciences.
Key Responsibilities
Build Snowflake-based knowledge engineering components using Snowflake warehouses Snowpark Cortex/AI capabilities Streams/Tasks Native Apps/Streamlit secure data sharing governance features APIs and cloud storage integrations.
Implement Snowflake semantic data pipelines graph enablement components ontology/schema pipelines vector and search integrations LLM grounding layers and governed access patterns.
Build Knowledge Graph components that contribute to transforming a clients data architecture.
Design develop configure test and implement AI and semantic solutions that integrate clearly with the broader enterprise system.
Work alongside project teams delivery leads engineers architects users use case representatives and UI designers to deliver assigned components of an end-to-end solution.




Build solid working relationships with client counterparts on the workstream and communicate implementation progress risks dependencies and technical findings clearly.
Help assemble supporting evidence for recommended semantic layer solutions including design rationale implementation notes validation inputs data quality observations and test outcomes.
Support sales solutioning demos accelerators or reusable assets when called upon by providing technical inputs or implementation examples.
Design evaluate maintain and deploy ontologies schemas mappings graph data models metadata structures validation rules and knowledge graph components as needed.
Keep developing skills in cutting-edge Data and AI solutions especially agentic technologies generative AI LLMs multimodal models semantic search graph RAG and knowledge graph approaches.
Share learnings with the team and help junior engineers understand practical development patterns engineering standards and knowledge graph implementation practices.
Required Qualifications
Bachelors degree or equivalent in Computer Science Information Technology Engineering Mathematics Data Science or a related field.
Minimum 2 years of experience with Knowledge Graph technologies such as RDF SPARQL LPG SHACL OWL graph query languages schema design ontology management and KG curation.
Minimum 2 years of experience in schema design ontology management semantic modeling taxonomy management metadata management and knowledge graph curation.
Minimum 2 years designing and developing Knowledge Graph solutions and graph-based ML models across functional and technical contexts.
Minimum 1 year of experience with end-to-end data pipeline implementation for AI applications especially LLM-enabled or enterprise knowledge applications with hands-on design and configuration.




Minimum 2 years of experience with relational databases object stores graph databases such as Stardog Neo4j Amazon Neptune or equivalent and vector databases.
No leadership or commercial ownership requirement at this band team lead exposure is positive to have.
Ability to work hands-on as a strong individual contributor while collaborating across project teams and delivery workstreams.
Required Skills/ Experience
Hands-on experience building Snowflake-enabled knowledge engineering solutions with warehouses Snowpark Cortex/AI capabilities Streams/Tasks Native Apps/Streamlit secure data sharing governance features APIs and cloud storage integrations.
2 years of Python and SQL experience with frameworks and tools such as TensorFlow PyTorch dbt SPARQL SHACL Apache Airflow Apache NiFi APIs and ETL pipeline development.
Practical experience with NLP and/or search techniques prompt engineering LLMs retrieval-augmented generation vector search semantic search and enterprise-scale AI application patterns.
Ability to formulate real-world problems into practical efficient and scalable AI and Knowledge Graph solution components on Snowflake.
Industry experience applying Snowflake-enabled knowledge engineering solutions in banking insurance healthcare retail communications manufacturing energy public services life sciences or another relevant domain.
Ability to build Snowflake-based components for semantic layer ontology graph vector search search retrieval and LLM grounding use cases.
Good to Have Skills
2 years of hands-on experience with cloud/data platforms with Snowflake specialization and exposure to AWS Azure or GCP in multi-cloud environments.
Snowflake certification or hands-on project experience in Snowflake data engineering Snowpark data cloud architecture or AI/data platform delivery.
Team lead exposure or readiness to guide junior engineers on project tasks.
External client-facing consulting experience including working with client stakeholders delivery teams or solutioning teams.
Broad experience in diverse ML techniques graph RAG agentic systems semantic search entity resolution multimodal models explainable AI and responsible AI practices.
Experience building reusable code components implementation templates design notes demos proof-of-concept assets runbooks or enablement material. AI Powered Tech Talent

📌 Neo4j (Bengaluru)
🏢 Accenture
📍 Bengaluru