Agentic AI Python Engineer: RAG & Vector DBs

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

Job summary

BeaconFire Inc. is seeking an Agentic AI Python Developer to build reliable AI agents and RAG workflows using Python, Flask, Django, and modern ML tooling. You’ll own end-to-end delivery from ingestion to deployment, including API design, evaluation, and monitoring.

The role emphasizes working with vector databases, graph databases, and cloud AI services like Vertex AI. Collaboration, code reviews, testing, and documentation are core expectations for this hands-on position.

Qualifications

• Lifecycle: development, testing, deployment.
• Relational DBs like MySQL/PostgreSQL.
• Experience with version control using Git.
• Experience building RAG solutions (hybrid search, chunking, reranking).
• Familiarity with agentic frameworks and tool/function calling patterns.
• Vector search concepts and at least one vector DB in production.

Responsibilities

• Design and develop high quality web apps using Python, Flask, Django.
• Write clean, maintainable code and ensure testability.
• Design and implement RAG pipelines on cloud platforms (Vertex AI, GCP).
• Build agentic workflows: tool use, planning, reflection, grounding.
• Develop end-to-end delivery: ingestion to deployment, APIs, monitoring.
• Conduct code reviews and testing to ensure reliability.
• Create technical docs and participate in planning and estimation.
• Stay current with Python technologies and best practices.

Skills

Python

Flask

Django

RAG pipelines

Vector DBs

Graph DBs

Git

RESTful APIs

AWS

Vertex AI

LangChain

Education

Master’s Degree in CS

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Job description

BeaconFire Inc. is seeking an Agentic AI Python Developer to build reliable AI agents and RAG workflows using Python, Flask, Django, and modern ML tooling. You’ll own end-to-end delivery from ingestion to deployment, including API design, evaluation, and monitoring.

The role emphasizes working with vector databases, graph databases, and cloud AI services like Vertex AI. Collaboration, code reviews, testing, and documentation are core expectations for this hands-on position.