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.
- Robust 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

📌 I&P - GN - SONG - AI & Data - Marketing - MMM RAG - Consultant (Bengaluru)
🏢 Accenture
📍 Bengaluru