Agentic AI Python Engineer for RAG & Vector DB

BeaconFire Inc.; Philadelphia (Philadelphia County); On-site; USD 120,000 - 180,000; Full time

Job summary

BeaconFire Inc. is seeking an Agentic AI Python Developer to build and deploy high-impact AI-powered web applications.

You will own end-to-end delivery, from ingestion to orchestration, with emphasis on RAG pipelines and agentic frameworks in a collaborative, growth-focused environment. The role requires strong Python web development skills (Flask/Django), experience with vector databases, and cloud services like GCP/AWS.

Qualifications

• Strong experience building RAG pipelines and agentic frameworks.
• Production-grade vector search with vector databases and tooling.
• Solid knowledge of Python web frameworks and REST APIs.
• Familiarity with CI/CD and cloud services for deployment.

Responsibilities

• Design and develop web applications using Python, Flask, Django.
• Write clean, maintainable code and ensure quality.
• Design and implement RAG pipelines on Google Cloud / Vertex AI.
• Build agentic workflows (tool use, planning, reflection).
• Perform code reviews, testing, and maintain technical docs.
• Participate in planning, estimation, and prioritization.
• Stay updated with Python technologies and security best practices.
• Ship APIs with monitoring, cost/performance optimization, and CI/CD.

Skills

Python

Flask

Django

LangGraph/LangChain

LlamaIndex

Vector databases

Git

RESTful API

AWS

Vertex AI

Google Cloud

PostgreSQL

MySQL

Education

Master’s Degree in Computer Science / Software Engineering

Tools

PostgreSQL

MySQL

Vertex AI

Google Cloud Platform

Job description

BeaconFire Inc. is seeking an Agentic AI Python Developer to build and deploy high-impact AI-powered web applications.

You will own end-to-end delivery, from ingestion to orchestration, with emphasis on RAG pipelines and agentic frameworks in a collaborative, growth-focused environment. The role requires strong Python web development skills (Flask/Django), experience with vector databases, and cloud services like GCP/AWS.