Description
Key Responsibilities
- Design and develop enterprise RAG applications using LLMs, embeddings, vector databases, and hybrid search.
- Build end-to-end document ingestion and knowledge ingestion pipelines for structured and unstructured data.
- Implement document parsing, chunking, metadata enrichment, embeddings, indexing, and retrieval strategies.
- Design and optimize semantic, vector, keyword, and hybrid search solutions.
- Develop RAG workflows incorporating query understanding, query rewriting, retrieval, reranking, context generation, and response generation.
- Work with LLMs such as Azure OpenAI, Anthropic Claude, or equivalent models.
- Develop agentic AI solutions using tools, function calling, MCP, and multi-agent/single-agent architectures where appropriate.
- Implement RAG evaluation and observability including retrieval quality, answer relevance, groundedness, hallucination detection, latency, and token/cost monitoring.
- Optimize RAG applications for accuracy, latency, scalability, and cost.
- Integrate RAG applications with enterprise systems, APIs, databases,



repositories, and knowledge sources.
- Develop secure APIs and backend services for AI applications.
- Collaborate with architects, developers, business analysts, and domain experts to translate business requirements into AI solutions.
- Establish best practices around prompt engineering, context management, guardrails, security, and responsible AI.
- Troubleshoot production issues and continuously improve the AI application based on user feedback and evaluation metrics.

Required Technical Skills

Generative AI / LLM
- Strong understanding of LLMs and Generative AI
- Prompt engineering and structured prompting
- LLM inference and model selection
- Function calling / tool calling
- Context-window management
- Understanding of hallucination and grounding challenges

RAG
- Robust hands-on experience building RAG applications
- Document ingestion and preprocessing
- Chunking strategies
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📌 DE&A - AIML - Data Science - Artificial Intelligence of Things (AIOT) (India)
🏢 Zensar Technologies
📍 India