Senior AI Engineer - LLM, RAG & Agentic AI Lead

Wipro; United Kingdom; On-site; GBP 90,000 - 140,000; Full time

Job summary

Wipro is seeking a Senior AI Engineer to design, build, and scale AI applications using LLMs, RAG, and Agentic AI frameworks. You will collaborate with product teams, data engineers, and stakeholders to deliver secure, production-ready AI solutions.

The role emphasizes building scalable backend services in Python, deploying with Docker/Kubernetes, and leading cross-functional architecture discussions to drive end-to-end AI delivery.

Qualifications

• Experience building AI applications with LLMs and Generative AI tech.
• Hands-on experience with AI orchestration frameworks.
• Production deployment of AI products from prototype to production.

Responsibilities

• Design and develop enterprise-grade AI applications leveraging LLMs and Generative AI technologies.
• Build and deploy Agentic AI workflows using LangChain, LangGraph, and LlamaIndex.
• Design and implement RAG architectures for knowledge-driven AI solutions.
• Develop intelligent agents capable of tool calling, memory management, reasoning, and workflow orchestration.
• Integrate AI services with enterprise systems via RESTful APIs and microservices.
• Develop scalable backend services using Python and asynchronous patterns.
• Design reusable AI components, SDKs, and services.
• Implement robust APIs with authentication, monitoring, and logging.
• Ensure software quality through testing and CI/CD pipelines.
• Deploy and manage AI applications using Docker and Kubernetes.
• Build cloud-native AI solutions on AWS, Azure, or GCP.
• Optimize model serving, inference, and cost efficiency.

Skills

Python

Asynchronous programming

CI/CD

Docker

Kubernetes

RESTful APIs

Microservices

Unit testing

LangChain

LlamaIndex

RAG

Cloud platforms

Tools

LangChain

LangGraph

LlamaIndex

Pinecone

Qdrant

Chroma

Docker

Kubernetes

Job description

Wipro is seeking a Senior AI Engineer to design, build, and scale AI applications using LLMs, RAG, and Agentic AI frameworks. You will collaborate with product teams, data engineers, and stakeholders to deliver secure, production-ready AI solutions.

The role emphasizes building scalable backend services in Python, deploying with Docker/Kubernetes, and leading cross-functional architecture discussions to drive end-to-end AI delivery.