Python AI Engineer

BeaconFire Inc.; Connecticut; 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-enabled web applications. You’ll own end-to-end delivery including ingestion, retrieval, agent orchestration, evaluation, and deployment.

The role emphasizes Python development with Flask/Django, experience with RAG pipelines, vector databases, and cloud services like Vertex AI. Work combines collaboration, growth, and reliable software delivery.

Qualifications

• Proficient in Python web frameworks and API development.
• Experience with RAG pipelines and vector databases.
• Familiar with cloud services, especially Vertex AI and GCP fundamentals.
• Knowledge of software testing, code quality, and CI/CD.

Responsibilities

• Collaborate to design and develop high quality web applications using Python, Flask, Django.
• Write clean, maintainable code and ensure reliability.
• Design and implement RAG pipelines on Google Cloud / Vertex AI.
• Build agentic workflows with tool use, planning, and guardrails.
• Ship APIs, monitoring, and security best practices.

Skills

Python

Flask

Django

Git

REST API

Vertex AI

LangChain/LangGraph

Vector databases

Education

Bachelor’s degree in CS or related field

Tools

Google Cloud

PostgreSQL

React/Next.js

Job description

We’re currently hiring for an exciting Agentic AI Python Developer role, and I wanted to reach out to see if you or someone in your network might be interested. This is a fantastic opportunity to work on high-impact projects using modern technologies in a collaborative and growth-oriented environment.

BeaconFire is based in Central NJ, specializing in Software Development, Web Development

and Business Intelligence; looking for a strong agentic AI developer who can build and

design reliable tool-using agents, and work comfortably with vector databases and graph databases. You'll own end-to-end delivery: ingestion, retrieval, agent orchestration, evaluation, and deployment.

Job Responsibilities

• Collaborate with the team to design and develop high quality Web applications using
• Python, Flask, Django, and related technologies.
• Write clean and efficient code, and ensure code maintainability and reusability.
• Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking,
• embeddings, indexing, retrieval, reranking, grounding).
• Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs)
• using Python-first frameworks.
• Perform code reviews to ensure code quality and consistency.
• Conduct testing to ensure application quality and reliability.
• Create and maintain technical documentation for web applications.
• Participate in project planning, estimation, and prioritization.
• Stay up to date with the latest technologies for Python development.
• Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding
• checks), and improve system quality iteratively.
• Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD,
• and security best practices.

Requirement

• Decent understanding of the software development/testing life cycle.
• Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc)slanguage skills
• Experience with version control tools, such as Git.
• Experience building RAG solutions (hybrid search, reranking, chunking strategies,
• Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex,
• Semantic Kernel, AutoGen) and tool/function calling patterns.
• Solid knowledge of vector search concepts and at least one vector DB in production.
• reliability mindset.

Preferred Qualifications

• Master's Degree in Computer Science, Software Engineering, or related field.
• 1+ year professional experience in Python web application development with either
• Flask or Django.
• Experience in RESTful API development in Python.
• Understanding of Python web application frameworks such as Flask or Django.
• Experience with Cloud services, such as AWS.
• Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, Cloud
• Run/GKE, storage).
• Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
• Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and
• Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses),
• Frontend integration (basic React/Next.js) or platform enablement (internal developer
• tooling).