- Experience
- Not specified
- Pay
- Not disclosed
- Education
- Not specified
- Location
- Gurgaon, India
- Work mode
- On-site
- Job type
- Full-time
About this role
Capgemini Engineering offers R&D and engineering services to innovative companies across industries. This role builds the data platforms behind AI products, including pipelines, digital twin and knowledge graph platforms, and feature stores that feed RAG and agent systems.
What you will do
- Build connectors for telemetry, topology, ITSM and knowledge sources
- Build ingestion, validation and data contract frameworks
- Develop network digital twin and topology graph platforms
- Build knowledge graphs, ontologies and semantic data models
- Develop feature engineering frameworks and feature stores
- Provide data foundations for RAG, GraphRAG and AI agents
- Implement metadata, lineage, observability and governance
What the employer expects
- Strong Python and SQL
- Data modeling, ETL/ELT and data architecture knowledge
- Hands-on with Spark, Spark Streaming and Kafka
- Experience with data lakes and AWS (S3, Glue, Lambda, SageMaker)
- Knowledge of ML, deep learning and generative AI
- Experience with relational, graph and vector databases
- MLOps, LLMOps and DataOps experience
Benefits
- Work on AI, GenAI, knowledge graph and digital twin technologies
- Exposure to enterprise-scale AI transformation
- Continuous learning across data engineering, GenAI and cloud
- Innovation-driven culture
Skills
- Python
- SQL
- Apache Spark
- Kafka
- AWS
- Knowledge Graphs
- RAG
- Vector Databases
- MLOps
- Data Lakes
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