Python AI Developer

Mphasis; San Francisco (CA); Presencial; USD 140.000 - 210.000; Jornada completa

Descripción de la vacante

Mphasis is seeking a Python AI Developer to design and implement AI-powered backend services in a scalable cloud environment. The role focuses on building data pipelines and microservices with Python, integrating GenAI capabilities, and deploying robust APIs.

The ideal candidate has extensive experience with LLMs, vector stores, and modern web frameworks, and brings strong MLOps and containerization skills to production-grade projects.

Formación

• 7+ years of software experience with Python.
• Experience with GenAI, NLP, and vector stores.
• Proficient in web frameworks (FastAPI, Flask, Django).
• Familiar with MLOps and containerization.

Responsabilidades

• 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.

Conocimientos

Python

GenAI/NLP

LLM frameworks

API development

Herramientas

Docker

FastAPI

Git

Descripción del empleo

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