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I&P - GN - SONG - AI & Data - Marketing - MMM RAG - Consultant
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and build end-to-end RAG pipelines, from ingestion to retrieval
Build multi-step, tool-using AI agents with LangChain or LlamaIndex
Integrate and orchestrate large language models for enterprise use cases
Deploy LLM solutions as APIs or microservices with scalability and observability
Implement evaluation frameworks for RAG and agent output quality
From the employer’s posting
Design and implement end-to-end RAG pipelines, including document ingestion, chunking, embedding, vector storage, and retrieval.
Build multi-step, tool-using AI agents using frameworks such as LangChain, LlamaIndex, or custom agent loops.
Integrate and orchestrate large language models (e.g., Gemini, GPT-4, Claude, Llama) for enterprise use cases.
Deploy LLM-based solutions as APIs or microservices, ensuring scalability and observability.
Implement evaluation frameworks to assess RAG and agent output quality (relevance, faithfulness, hallucination rate).
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 3, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Accenture is hiring
202 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is picking up
- Takes jobs down quickly
- 11% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Azure
- Docker
- GCP
- Kubernetes
- MLflow
- FastAPI
- Hugging Face
Where the posting names them
• Collaborate with clients to identify AI use cases and translate requirements into production-ready agent architectures. 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
• 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.
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 Experience: Minimum 3 year(s) of experience is required
• 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:
Your next step
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Has Accenture posted this job before?
Yes. We’ve followed one other I&P - GN - SONG - AI & Data - Marketing - MMM RAG - Consultant job there since October 2026. It came down after 1 day.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
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.
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
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
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.
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
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.
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Bengaluru
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