Artificial Intelligence Engineer

BeaconFire Inc.; New Jersey; On-site; USD 110,000 - 160,000; Full time

Job summary

BeaconFire Inc. in Central New Jersey is seeking a skilled AI developer to design and productionize Vertex AI–based RAG systems and tool-using agents.

You will own end-to-end delivery from ingestion to deployment, collaborating on Python web applications (Flask/Django), vector databases, and cloud pipelines, with emphasis on reliability and scalable engineering practices.

Qualifications

• Experience designing and productionizing AI/ML pipelines (RAG and tool use).
• Strong Python coding, testing, and code quality practices.
• Knowledge of vector databases and graph databases in production.

Responsibilities

• Design and implement RAG pipelines on Vertex AI (embedding, indexing, retrieval).
• Build agentic workflows with tool use, planning, and guardrails.
• Own end-to-end delivery: ingestion, retrieval, orchestration, evaluation, deployment.
• Collaborate on web applications using Python frameworks (Flask/Django).
• Conduct testing, reviews, and documentation; drive CI/CD and security best practices.

Skills

Python

Flask

Django

REST APIs

Git

Vector search

RAG

LangChain

LangGraph

LlamaIndex

Semantic Kernel

AutoGen

Vertex AI

Cloud / GCP fundamentals

Kubernetes

CI/CD

Education

Master’s Degree in Computer Science or related

Bachelor’s Degree in Computer Science or related

Tools

Vertex AI

Google Cloud

PostgreSQL/MySQL

Docker

Kubernetes

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 productionize Vertex AI–based RAG systems (Vertex AI Search / Vertex AI RAG patterns), 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) language 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.
• Solid knowledge of vector search concepts and at least one vector DB in production. Strong engineering practices: code reviews, testing, telemetry, secure-by-design, and 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 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).