NC
AI Engineer
NR Consulting - India
- 🇮🇳 India
- On-site
- 15 hours ago
- AI
- RAG
- Vector Search
- OpenAI
- Azure OpenAI
- Machine Learning
- Azure
- AWS
- GCP
- MLOps
- Pinecone
- Weaviate
- Chroma
- Qdrant
- Azure AI
- Elasticsearch
- LangChain
- LlamaIndex
- Semantic Kernel
- Neo4j
- Python
- AI/ML
- Data Modeling
- Docker
- Kubernetes
15 hours ago
Location: Bangalore
Exp: 7+ Years
Job Description:
Key Responsibilities
- Design and develop end-to-end RAG solutions using enterprise knowledge sources.
- Build and maintain semantic ontologies, taxonomies, and knowledge graphs to enhance information retrieval and reasoning.
- Implement document ingestion, chunking, indexing, embedding generation, and vector search pipelines.
- Integrate LLMs (OpenAI, Azure OpenAI, Anthropic, Llama, etc.) with enterprise applications.
- Develop and optimize semantic search, hybrid search, and contextual retrieval mechanisms.
- Create metadata models and ontology frameworks that improve data discoverability and interoperability.
- Evaluate and improve RAG performance through prompt engineering, retrieval optimization, reranking, and grounding techniques.
- Collaborate with domain experts to translate business requirements into ontology and AI-driven solutions.
- Establish governance, accuracy, and quality measurement frameworks for GenAI applications.
- Deploy AI solutions on Azure, AWS, or GCP using modern MLOps practices.
• Strong experience in building and deploying RAG-based applications.
• Hands-on experience with Vector Databases such as Pinecone, Weaviate, Chroma, Qdrant, Azure AI Search, or Elasticsearch.
• Expertise in GenAI frameworks such as LangChain, LlamaIndex, Semantic Kernel, or Haystack.
• Experience designing and managing Ontologies, Taxonomies, and Knowledge Graphs.
• Knowledge of RDF, OWL, SKOS, SPARQL, Protégé, Neo4j, GraphDB, or similar semantic technologies.
• Proficiency in Python and AI/ML development frameworks.
• Strong understanding of embeddings, transformer models, semantic search, and information retrieval techniques.
• Experience with Azure OpenAI, OpenAI APIs, or equivalent LLM platforms.
• Familiarity with data modeling, metadata management, and knowledge management systems.
• Experience with containerization and cloud-native deployments (Docker, Kubernetes).
AI Engineer · NR Consulting - India