Agentic AI Engineer (Python)

BeaconFire Inc.; New Jersey; On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive pay

Growth opportunities

Cutting-edge AI projects

Job summary

BeaconFire Inc. in New Jersey seeks an Agentic AI Engineer to design and productionize advanced AI systems using modern RAG and agent-based architectures on Google Cloud Vertex AI.

You will own end-to-end development of RAG pipelines, ingestion and retrieval systems, agent orchestration, evaluation, and deployment, collaborating across engineering teams to ship production-grade AI solutions. Strong Python, ML tooling, and cloud experience are required, with a focus on scalable web apps using

Qualifications

• Must have strong Python experience and lifecycle understanding.
• Experience with relational databases (MySQL, PostgreSQL).
• Familiarity with cloud platforms (AWS or GCP) and Vertex AI.

Responsibilities

• Design and build Python web applications using Flask or Django.
• Develop and optimize RAG pipelines (chunking, embeddings, indexing, retrieval, reranking).
• Create agentic workflows (tool usage, planning, guardrails, outputs).
• Review code for maintainability and reliability.
• Test to ensure system reliability and performance.
• Document technical work and participate in planning.
• Define evaluation frameworks (retrieval metrics, hallucination checks).
• Deploy production systems (APIs, CI/CD, monitoring, security).

Skills

Python

AI/ML experience

RAG pipelines

Vertex AI

LangChain / LangGraph

Semantic Kernel

AutoGen

Vector search

testing

secure design

reliability mindset

Flask

Django

RESTful APIs

GCP/AWS

graph-based RAG

Pub/Sub / Kafka

evaluation tools (RAGAS, TruLens)

React / Next.js

Education

Master’s degree in Computer Science or related field

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

Vector database

Job description

Job Title: Agentic AI Engineer (Python)

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)
• 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.