I&P - GN - SONG - AI & Data - Marketing - MMM RAG - Consultant
Quick Summary
• 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,
• Must Have Skills: Proficiency in RAG architecture design, LLM integration, AI agent development,
Requirements
~1 min readVisit us at www.accenture.com
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.
Responsibilities
~1 min read• 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.
• 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.
• 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.
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Location & Eligibility
Listing Details
- Posted
- October 7, 2026
- First seen
- October 8, 2026
- Last seen
- October 10, 2026
Posting Health
- Days active
- 3
- Repost count
- 0
- Trust Level
- 32%
- Scored at
- October 12, 2026
Signal breakdown
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