AI Lead: Generative AI & Agentic AI

9NEXUS Limited; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

9NEXUS Limited is seeking an experienced AI Lead to drive the design, development, and deployment of enterprise GenAI solutions. You will lead GenAI applications, intelligent assistants, and AI chatbots, and design end-to-end AI pipelines for real-world data sources.

You will work with LangChain, LangGraph, and related frameworks to build scalable AI systems, deploy on AWS and Azure, and ensure responsible AI practices while collaborating with stakeholders to guide technical implementation.

Qualifications

• 10+ years of IT experience with 4+ years in AI/ML and GenAI.

Responsibilities

• Lead the development of enterprise GenAI applications, intelligent assistants, and AI chatbots.
• Design and optimize RAG pipelines, embeddings, vector search, and document Q&A systems.
• Build agentic AI and multi-agent workflows using LangChain, LangGraph, CrewAI, or AutoGen.
• Develop backend services and REST APIs using Python, FastAPI, or Flask.
• Integrate LLMs such as GPT and LLaMA with enterprise applications and data sources.
• Deploy and optimize AI solutions on AWS or Azure.
• Drive model evaluation, prompt engineering, performance optimization, and responsible AI practices.
• Collaborate with stakeholders and guide technical implementation.

Skills

Python

Machine Learning

Deep Learning

NLP

Generative AI

LLMs

RAG

Agentic AI

LangChain

LangGraph

Vector databases

FastAPI

Flask

REST APIs

AWS

Azure

Tools

FAISS

Pinecone

ChromaDB

Docker

Kubernetes

CI/CD

Job description

Experience: 10+ years overall IT experience, with 4+ years in AI/ML and GenAI

We are looking for an experienced AI Lead to drive the design, development, and deployment of enterprise AI solutions using Generative AI, LLMs, RAG, and Agentic AI.

Key Responsibilities:

• Lead the development of enterprise GenAI applications, intelligent assistants, and AI chatbots.


• Design and optimize RAG pipelines, embeddings, vector search, and document Q&A systems.


• Build agentic AI and multi-agent workflows using LangChain, LangGraph, CrewAI, or AutoGen.


• Develop backend services and REST APIs using Python, FastAPI, or Flask.


• Integrate LLMs such as GPT and LLaMA with enterprise applications and data sources.


• Deploy and optimize AI solutions on AWS or Azure.


• Drive model evaluation, prompt engineering, performance optimization, and responsible AI practices.


• Collaborate with stakeholders and guide technical implementation.

Required Skills:

• Python, Machine Learning, Deep Learning, NLP


• Generative AI, LLMs, RAG, and Agentic AI


• LangChain, LangGraph, or equivalent frameworks


• Vector databases: FAISS, Pinecone, ChromaDB, or similar


• FastAPI / Flask and REST API integration


• AWS / Azure AI services


• LLM evaluation, prompt engineering, and production deployment

Good to Have: MCP, Azure OpenAI, Docker, Kubernetes, CI/CD, and enterprise AI solution delivery.