I&P - GN - SONG - AI & Data - Marketing - MMM RAG - Consultant

Accenture; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Accenture is seeking a Data Engineering Consultant focused on RAG, LLMs, and AI agent development. You will design and build intelligent AI applications that use retrieval-augmented generation and autonomous agents.

Your day-to-day includes assembling RAG pipelines, tuning LLMs, and creating multi-step agents with LangChain, deploying them in scalable production environments. You will collaborate with data and ML engineers to deliver AI-powered products that drive measurable business value,

Qualifications

• Minimum 3 year(s) experience in relevant field.
• B.Tech/BE/MCA or equivalent in CS/AI/ML.
• Must have: RAG architecture design, LLM integration, AI agent development.

Responsibilities

• Design end-to-end RAG pipelines including ingestion, embedding, and retrieval.
• Integrate and orchestrate large language models for enterprise use cases.
• Build multi-step AI agents using LangChain or similar frameworks.
• Develop and optimize prompt-engineering strategies for accuracy and latency.
• Configure vector databases for semantic search and retrieval.
• Evaluate RAG/agent outputs for relevance and faithfulness.
• Deploy LLM-based solutions as scalable APIs/microservices.

Skills

RAG design

LLM integration

AI agent dev

Python

LangChain

Vector DBs

Prompt engineering

Education

B.Tech/BE/MCA

Tools

LangChain

LlamaIndex

Docker

Kubernetes

FastAPI

Vertex AI

AWS Bedrock

Azure OpenAI

Job description

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.
• Strong 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.

Qualification

• Experience:Minimum 3 year(s) of experience is required
• Educational Qualification:B.Tech/BE/MCA or equivalent in Computer Science, AI/ML, or related field