Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Develop and integrate features across AI platforms including RAG pipeline and prompt tuning with focus on GraphRAG dynamic query, graph-aware retrieval, and knowledge-graph schema evolution.
Validate sprint-level deliverables against golden dataset baselines and coordinate on design and integration with AI architect, backend, and KG validation teams.
Deliver orchestration component integration managing RAG-layer retrieval pipeline to drive agent selection, routing, and response generation.
Minimum Requirements
6+ years of AI engineering experience with strong Python programming skills.
3+ years hands-on experience with RAG/GraphRAG implementation including vector store integration and orchestration integration.
Experience with SPARQL, graph-aware retrieval, ontology mapping, semantic disambiguation, and building or validating golden Q&A datasets for LLM grounding.
Education: B.Tech or MCA in Computer Science, AI/ML, or related field, or equivalent practical experience.
Ideal Candidate Profile
Experienced in regulated or enterprise AI product environments with track record replacing template-based SPARQL with GraphRAG.
Comfortable working within sprint-based scoped dataset expansions rather than open-ended tuning, validating against capped golden datasets.
Able to author forward-looking technical design documents and coordinate across multidisciplinary teams including AI architects and knowledge graph validation.