Junior Python AI Engineer

BeaconFire Inc.; Pennsylvania; On-site; USD 110,000 - 170,000; Full time

Job summary

BeaconFire Inc. is seeking a strong AI developer to design reliable tool-using agents and work with vector and graph databases. You will own end-to-end delivery including ingestion, retrieval, orchestration, evaluation, and deployment.

Responsibilities cover building Web apps with Python stacks, implementing RAG pipelines on Vertex AI, and developing agentic workflows with strong testing and documentation practices. Cloud experience and code quality are essential.

Qualifications

• Solid understanding of SDLC and testing life cycle.
• Experience with vector search concepts and production vector DBs.
• Experience building RAG solutions and agentic frameworks.
• Familiarity with cloud services and API development.
• Strong code quality, reviews, and documentation habits.

Responsibilities

• Design and develop web apps using Python, Flask, Django.
• Build agentic workflows with tool use, planning, and grounding.
• Create RAG pipelines on Google Cloud / Vertex AI.
• Own end-to-end delivery from ingestion to deployment.
• Write tests, perform code reviews, and ensure reliability.
• Document architecture and participate in planning/estimation.

Skills

Python

Web development

RAG pipelines

Vector databases

Graph databases

Git

LangChain/LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Education

Master's Degree in CS/SE (preferred)

Tools

Vertex AI

Google Cloud

AWS

PostgreSQL

MySQL

Git

Job description

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).