Principal Data Architect

Capgemini; Pune District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Capgemini in Pune, India, seeks a Principal Knowledge & Data Platform Lead to architect knowledge graphs, retrieval, and context foundations for safe AI in regulated environments. Lead enterprise graph design, RAG optimization, context engineering, and AI knowledge management, with memory platforms across AI systems.

Required: Neo4j, graph modeling, embeddings, vector databases, and domain experience in financial services or healthcare.

Qualifications

• Deep expertise in Knowledge Graphs, Ontologies, and Semantic Data Modeling.
• Proven experience building and scaling production-grade RAG systems.
• Strong understanding of GraphRAG, Hybrid Retrieval, Embedding Strategies, and Retrieval Evaluation.
• Experience with Context Engineering, Agent Memory, and Agentic AI architectures.
• Knowledge management expertise focused on AI consumption in regulated environments.
• Experience in regulated industries like Financial Services, Banking, Insurance, Healthcare or GDPR-governed environments.

Responsibilities

• Architect, model, and retrieve with knowledge graphs and ontologies.
• Optimize RAG end-to-end, embeddings, hybrid search, and grounding quality.
• Define Context Engineering to control what information enters an agent's context window.
• Oversee AI Knowledge Management lifecycle: curation, provenance, governance, and auditability.
• Lead agent memory platforms for episodic and long-term memory across AI systems.
• Enforce permissioned retrieval with tenant isolation and audit trails.
• Transform production data into training assets for future LLM/SLM development.

Skills

Knowledge Graphs

Ontologies

Semantic Data Modeling

RAG

Context Engineering

AI Knowledge Management

Enterprise Data Platforms

GraphRAG

Agent Memory

AI Platform Engineering

Financial Services Domain

Healthcare Domain

Tools

Neo4j

Vector Databases

Job description

We are seeking a Principal Knowledge & Data Platform Lead to architect the knowledge, retrieval, and context foundation that enables AI agents to reason, retrieve, learn, and operate safely in highly regulated environments.

About the Role

This is a high-impact individual contributor role for a senior technologist who combines deep expertise in Knowledge Graphs, RAG, Context Engineering, AI Knowledge Management, and Enterprise Data Platforms.

Responsibilities

• Enterprise Knowledge Graph architecture, ontology design, semantic modeling, and graph-based retrieval
• End-to-end RAG optimization including embeddings, hybrid search, GraphRAG, reranking, retrieval evaluation, and grounding quality
• Context Engineering frameworks that determine what information enters an agent's context window, when, and at what cost
• AI Knowledge Management lifecycle covering curation, provenance, versioning, freshness, governance, and auditability
• Agent Memory platforms supporting episodic and long-term memory across AI systems
• Permission-aware retrieval with tenant isolation, document-level security, compliance controls, and audit trails
• Data flywheel architecture transforming production data into training and evaluation assets for future LLM and SLM development

Preferred Skills

• Deep expertise in Neo4j, Knowledge Graphs, Ontologies, and Semantic Data Modeling
• Proven experience building and scaling production-grade RAG systems
• Strong understanding of GraphRAG, Hybrid Retrieval, Embedding Strategies, and Retrieval Evaluation
• Experience with Context Engineering, Agent Memory, and Agentic AI architectures
• Knowledge management expertise focused on AI consumption rather than traditional enterprise search
• Experience working within regulated industries such as Financial Services, Banking, Insurance, Healthcare, or GDPR-governed environments
• Technical leadership ability to define standards, influence architecture decisions, and drive adoption across multiple engineering teams
• Vector Databases, Enterprise Search, AI Observability
• LLM Evaluation Frameworks
• AI Platform Engineering & Agentic AI Systems
• Financial Services, Payments, Insurance, or Healthcare Domain Experience