Job Title
- Data Engineering Consultant
- RAG, LLM & AI Agents | S&C; Management Level: 09
- Consultant

Location:
PAN India Must Have

Skills:
Retrieval-Augmented Generation (RAG), Large Language Models (LLM), AI Agent Development, Python, LangChain, Vector Databases (Pinecone/Weaviate/ChromaDB), Prompt Engineering Good to Have

Skills:
LlamaIndex, FastAPI, Vertex AI / AWS Bedrock / Azure OpenAI, HuggingFace, Embedding Models, Docker / Kubernetes, MLflow Job Summary: As a Data Engineering Consultant specializing in RAG, LLMs, and AI Agent development, you will be responsible for designing and building intelligent, context-aware AI applications that leverage retrieval-augmented generation architectures and autonomous agent frameworks. Your typical day will involve developing RAG pipelines, fine-tuning and integrating LLMs, building multi-step AI agents using LangChain, and deploying these solutions in scalable production environments. You will work closely with data engineers, ML engineers, and product teams to deliver AI-powered products that create measurable business value. Roles &

Responsibilities:
• Design and implement end-to-end RAG pipelines, including document ingestion, chunking, embedding, vector storage, and retrieval.
• Integrate and orchestrate large language models (e.g., Gemini, GPT-4, Claude, Llama) for enterprise use cases.
• Build multi-step, tool-using AI agents using frameworks such as LangChain, LlamaIndex, or custom agent loops.
• Develop and optimize prompt engineering strategies for accuracy,



reliability, and latency.
• Select and configure vector databases (e.g., Pinecone, Weaviate, ChromaDB) for semantic search and retrieval.
• Implement evaluation frameworks to assess RAG and agent output quality (relevance, faithfulness, hallucination rate).
• Deploy LLM-based solutions as APIs or microservices, ensuring scalability and observability.
• Collaborate with clients to identify AI use cases and translate requirements into production-ready agent architectures. Professional & Technical

Skills:
• Must Have

Skills:
Proficiency in RAG architecture design, LLM integration, AI agent development, vector databases and prompt engineering
• Hands-on experience with orchestration frameworks such as LangChain or LlamaIndex.
• Strong Python skills for building and deploying LLM pipelines and agent workflows.
• Experience with vector databases and embedding models for semantic retrieval.
• Solid grasp of prompt engineering
- few-shot learning, and chain-of-thought techniques.
• Knowledge of LLM evaluation metrics and tools (e.g., RAGAS, TruLens, or custom eval pipelines).
• Experience deploying AI services on cloud platforms (GCP Vertex AI, AWS Bedrock, or Azure OpenAI) is an advantage. Additional Information:
• The ideal candidate will have a passion for applied AI and a track record of delivering LLM-powered solutions in production environments.
• This position is based at PAN India offices. About Our Company | Accenture

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