GenAI Developer

9nexus; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

9nexus is seeking experienced AI/GenAI professionals to design and develop AI/GenAI solutions using Python, LLMs, and modern tooling. You will build scalable APIs and backend services, integrating AI models with enterprise databases and deploying on major clouds.

The role requires hands-on experience with RAG pipelines, LangChain, vector databases, and REST APIs, with collaboration across cross-functional teams to deliver scalable AI applications.

Qualifications

• Experience designing AI/GenAI solutions using LLMs and modern AI tooling.
• Proven ability to build scalable APIs and backend services.
• Experience deploying AI solutions on cloud platforms.

Responsibilities

• Design and develop AI/GenAI solutions using LLMs.
• Build and optimize RAG pipelines and AI agents.
• Develop APIs and backend services using Python and FastAPI.
• Integrate AI models with enterprise applications and databases.
• Deploy AI solutions on Azure/AWS/GCP.
• Collaborate with cross-functional teams to deliver scalable AI applications.

Skills

Python

Generative AI

LLMs

RAG

Prompt Engineering

Machine Learning

SQL

Tools

FastAPI

REST APIs

Azure OpenAI / Azure AI Services

LangChain

LangGraph

Vector Databases

Pinecone

Chroma

FAISS

Weaviate

Job description

We are looking for experienced AI/GenAI professionals with strong expertise in Python, Large Language Models (LLMs), Generative AI, and Machine Learning.

Key Skills

• Python
• Generative AI (GenAI)
• LLMs (GPT, Claude, Gemini, Llama, etc.)
• RAG (Retrieval-Augmented Generation)
• Prompt Engineering
• FastAPI / REST APIs
• Azure OpenAI / Azure AI Services
• LangChain / LangGraph
• Vector Databases (Pinecone, Chroma, FAISS, Weaviate)
• Machine Learning
• SQL

Responsibilities

• Design and develop AI/GenAI solutions using LLMs.
• Build and optimize RAG pipelines and AI agents.
• Develop APIs and backend services using Python and FastAPI.
• Integrate AI models with enterprise applications and databases.
• Deploy AI solutions on Azure/AWS/GCP.
• Collaborate with cross-functional teams to deliver scalable AI applications.