GenAI Python Developer - Production AI & MLOps

Mphasis; Berkeley Heights (NJ); On-site; USD 120,000 - 170,000; Full time

Job summary

Mphasis is seeking an AI Developer with Python to build production-grade Generative AI applications and GenAI-enabled solutions. You will work on RAG, AI agents, and back-end APIs, integrating LLMs with vector databases and external services in enterprise contexts.

The role emphasizes Python excellence, experience with LangChain and modern AI tooling, and building scalable data pipelines and microservices. Onsite work at client sites or offices is expected, with full-time responsibilities.

Qualifications

• Hands-on experience building production-grade Generative AI applications.
• Deep Python expertise with enterprise LLM integrations and vector databases.
• Experience designing backend APIs, microservices, and data pipelines.

Responsibilities

• Design and develop AI/GenAI-driven applications using Python.
• Build scalable backend APIs, microservices, and data pipelines.
• Develop and implement Retrieval-Augmented Generation (RAG) solutions.
• Build and orchestrate AI/LLM agents using LangChain, LangGraph, CrewAI, or similar frameworks.
• Integrate LLMs with enterprise applications, vector databases, and REST APIs.
• Implement prompt engineering and NLP solutions for enterprise use cases.
• Develop backend services using FastAPI, Flask, or Django.
• Optimize application performance and build production-ready solutions.
• Containerize applications using Docker and support deployment to AWS, Azure, or GCP.
• Follow software engineering and MLOps practices including Git/version control, CI/CD, testing, monitoring, and deployment.

Skills

Python

Generative AI

RAG

AI agents

NLP

MLOps

CI/CD

Tools

LangChain

LangGraph

CrewAI

Docker

FastAPI

Flask

Django

Vector databases

AWS

Azure

GCP

Job description

Mphasis is seeking an AI Developer with Python to build production-grade Generative AI applications and GenAI-enabled solutions. You will work on RAG, AI agents, and back-end APIs, integrating LLMs with vector databases and external services in enterprise contexts.

The role emphasizes Python excellence, experience with LangChain and modern AI tooling, and building scalable data pipelines and microservices. Onsite work at client sites or offices is expected, with full-time responsibilities.