Artificial Intelligence Engineer

BeaconFire Inc.; Philadelphia (Philadelphia County); On-site; USD 110,000 - 160,000; Full time

Job summary

BeaconFire Inc. seeks an experienced Python web developer to build scalable web applications using Flask/Django. You will design RAG pipelines on Vertex AI, implement agentic workflows, and own code quality through reviews, testing, and documentation.

You will collaborate with cross-functional teams, estimate work, and stay current with Python technologies, while delivering robust APIs and production-grade features.

Qualifications

• Decent understanding of the software development/testing life cycle.
• Knowledge of relational databases (e.g. MySQL, PostgreSQL).
• Experience with version control tools, such as Git.
• Experience building RAG solutions (hybrid search, reranking, chunking, embeddings, prompt + schema design).
• Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool calling patterns.

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 using Python-first frameworks and ensure proper tool use, planning, reflection/guardrails.
• 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 checks), and improve system quality iteratively.
• Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.

Tools

Python/Web development (Flask/Django)

Git

RAG solutions

Agentic frameworks

Vertex AI / GCP

LangChain/LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Pub/Sub / Kafka

Job description

• 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, embeddings, prompt + schema design).
• Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.

Preferred Qualifications:

• 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 multilingual retrieval.
• Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
• Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).