AI Developer with Python
Senior (7+ yrs) Python AI developer building production-grade GenAI applications: RAG pipelines, LLM agents with LangChain/LangGraph/CrewAI, backend APIs and microservices in FastAPI/Flask/Django, containerized with Docker and deployed to AWS/Azure/GCP with MLOps practices. Onsite 5 days/week in Sunnyvale, CA or Berkeley Heights, NJ.
- Compensation
- Not disclosed
- Location
- Berkeley Heights, United States
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- 7+ years of experience
- Deep Python expertise
- Hands-on experience building production-grade Generative AI applications
- Experience developing Retrieval-Augmented Generation (RAG) solutions
- Experience building/orchestrating AI/LLM agents with LangChain, LangGraph, CrewAI or similar frameworks
- Practical experience integrating LLMs with enterprise applications, vector databases, and external/REST APIs
- Experience building scalable backend APIs, microservices, and data pipelines
- Backend development with FastAPI, Flask, or Django
- Prompt engineering and NLP for enterprise use cases
- Containerizing applications with Docker and deploying to AWS, Azure, or GCP
- Software engineering and MLOps practices: Git/version control, CI/CD, testing, monitoring, deployment
- Able to work onsite 5 days per week from day 1
- Available for mandatory in-person interview
Full description
AI Developer with PythonLocations: Sunnyvale, CA / Berkeley Heights, NJ
Work Model: 5 Days Onsite from Day 1 Interview: Mandatory In-Person InterviewExperience: 7+ Years
Check out the role overview below If you are confident you have got the right skills and experience, apply today.
Job Summary
We are looking for a strong Python AI Developer with hands-on experience building production-grade Generative AI applications, RAG solutions, AI agents, backend APIs, and microservices. The ideal candidate should have deep Python expertise and practical experience integrating LLMs with enterprise applications, vector databases, and external APIs.
Key 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. xhmxlyz
- Follow software engineering and MLOps practices including Git/version control, CI/CD, testing, monitoring, and deployment.