Mphasis
AI ML Developer with Python
Designs and builds AI-driven applications, data pipelines, and microservices in Python, implementing RAG pipelines and LLM-based agents with tools like LangChain, LangGraph, or CrewAI, and deploying via Docker to AWS/Azure/GCP. Requires 7+ years of software experience with deep Python skills.
- Compensation
- Not disclosed
- Location
- Berkeley Heights, United States
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 7+ years of total software experience
- Deep proficiency in Python
- Hands-on experience with GenAI, NLP, prompt engineering, and vector stores
- Implement Retrieval-Augmented Generation (RAG)
- Orchestrate AI agents using tools like LangChain, LangGraph, or CrewAI
- Knowledge of web frameworks such as FastAPI, Flask, or Django
- Integrate LLMs with enterprise vector databases and external REST APIs
- Deploy production-ready code via Docker and cloud platforms (AWS, Azure, GCP)
Nice to have
- Familiarity with MLOps practices
- Git version control
- Containerization
Full description
A Python AI Developer job description requires strong programming skills, Generative AI expertise, and backend API development. Key requirements typically include Python proficiency, LLM frameworks, and cloud deployment.
Key Responsibilities
- Design and build AI-driven applications, data pipelines, and microservices using Python.
- Implement Retrieval-Augmented Generation (RAG) and orchestrate AI agents using tools like LangChain, LangGraph, or CrewAI.
- Integrate Large Language Models (LLMs) with enterprise vector databases and external REST APIs.
- Optimize backend performance and deploy production-ready code via Docker and cloud platforms (AWS, Azure, GCP).
Required Skills
- 7+ years of total software experience with deep proficiency in Python.
- Hands-on experience with GenAI, NLP, prompt engineering, and vector stores.
- Knowledge of web frameworks such as FastAPI, Flask, or Django.
Familiarity with MLOps practices, Git version control, and containerization