Python AI Developer – GenAI / Agentic AI

BeaconFire Inc.; New Jersey; On-site; USD 120,000 - 180,000; Full time

Job summary

BeaconFire Inc., a New Jersey-based technology consulting firm, seeks an Agentic AI Engineer to design and productionize advanced AI systems using RAG and agent-based architectures on Google Cloud Vertex AI.

You will own end-to-end development of RAG-based AI systems, including ingestion, retrieval, orchestration, evaluation, and deployment. Proficiency in Python, Flask/Django, and cloud services is required.

Qualifications

• Proficient in Python development with strong testing practices.
• Experience with relational databases (MySQL, PostgreSQL).
• Knowledge of agentic frameworks like LangChain, LangGraph, Semantic Kernel, AutoGen.
• Experience with vector search and at least one vector database.
• Experience building RESTful APIs and cloud deployment.

Responsibilities

• Design and develop web applications using Python, Flask, and Django.
• Build and optimize RAG pipelines (embedding, indexing, retrieval, reranking).
• Develop agentic workflows (tool usage, planning, guardrails, outputs).
• Conduct code reviews and ensure maintainable, reusable code.
• Perform testing to ensure system reliability and performance.
• Create and maintain technical documentation.
• Collaborate on project planning, estimation, prioritization.
• Define and run evaluation frameworks for retrieval and QA.
• Deploy production systems (APIs, CI/CD, monitoring, security).

Skills

Python development

Software development lifecycle

Testing practices

Relational databases

Vector search concepts

Evaluation & monitoring

Documentation

Education

Master's degree in Computer Science or related field

Tools

Flask

Django

Git

LangChain

LangGraph

Semantic Kernel

AutoGen

Vector databases

React/Next.js

Google Cloud Vertex AI

GCP services (IAM, Cloud Run, GKE)

Pub/Sub

Kafka

Job description

BeaconFire Inc. is a New Jersey-based technology consulting firm specializing in software development, web development,and business intelligence solutions. We are seeking a skilled Agentic AI Engineer to design and productionize advanced AI systems using modern RAG and agent-based architectures.

As an Agentic AI Engineer, you will own the end-to-end development of RAG-based AI systems on Google Cloud Vertex AI. This includes ingestion pipelines, retrieval systems, agent orchestration, evaluation, and deployment. You will work with modern AI frameworks and databases to build scalable, production-ready intelligent systems.

• Design and develop high-quality web applications using Python, Flask, and Django
• Build and optimize RAG pipelines (chunking, embeddings, indexing, retrieval, reranking, grounding)
• Develop agentic workflows (tool usage, planning, guardrails, structured outputs)
• Conduct code reviews and ensure maintainable, reusable code
• Perform testing to ensure system reliability and performance
• Create and maintain technical documentation
• Collaborate on project planning, estimation, and prioritization
• Define and run evaluation frameworks (retrieval metrics, hallucination checks, answer quality)
• Deploy production systems (APIs, CI/CD, monitoring, cost optimization, security best practices)

Basic Qualifications

• Strong experience in Python (Python 3) development
• Understanding of software development lifecycle and testing practices
• Knowledge of relational databases (e.g., MySQL, PostgreSQL)
• Experience with version control tools like Git
• Familiarity with at least one agentic framework such as:
• LangChain / LangGraph
• Semantic Kernel
• AutoGen
• Solid understanding of vector search and experience with at least one vector database
• Strong engineering practices (testing, telemetry, secure design, reliability mindset)
• Master's degree in Computer Science or related field
• Experience with Flask or Django web frameworks
• Experience building RESTful APIs
• Familiarity with cloud platforms such as AWS or GCP
• Experience with Google Cloud Vertex AI and GCP services (IAM, Cloud Run, GKE, logging/monitoring)
• Knowledge of graph-based RAG (entity linking, traversal, retrieval fusion)
• Experience with streaming tools (Pub/Sub, Kafka) and document pipelines
• Familiarity with evaluation tools (RAGAS, TruLens) and prompt/version management
• Exposure to frontend frameworks (React, Next.js) or internal tooling
• Competitive compensation and growth opportunities
• Collaborative and innovative team environment
• Work on cutting-edge AI and LLM systems
• Opportunity to build production-grade agentic AI solutions.