Gen AI Rules Engine Engineer

Tech Mirrors

Woodbridge Township (NJ)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Tech Mirrors is hiring a Rules Engine Engineer to design and build a next-gen rule engine platform onsite in Iselin, NJ. The role focuses on integrating Gen AI for dynamic rule generation, leveraging graph data and data science models to detect patterns, and building robust APIs for enterprise integration.

The ideal candidate will have experience with rule engines, Gen AI frameworks, Python/Java, and graph databases, contributing to scalable, explainable AI-driven decisions.

Qualifications

  • Experience in building rule engines/decisioning systems.
  • Hands-on experience with Gen AI/LLM frameworks (OpenAI, Azure OpenAI, LangChain).
  • Proficiency in Python and/or Java and microservices architecture.
  • Familiarity with graph databases and pattern detection.
  • Experience with data science concepts and model integration.

Responsibilities

  • Design and build a next-gen rule engine platform from scratch.
  • Integrate Gen AI to dynamically generate and optimize rules.
  • Leverage graph data and data science models to detect patterns and relationships.
  • Develop rule evaluation, orchestration, and decisioning frameworks.
  • Build APIs and services for rule execution and integration with enterprise systems.
  • Ensure scalability, performance, and explainability of AI-driven decisions.

Skills

Gen AI
Python/Java
Microservices
Graph databases
Data science

Education

Bachelor's degree

Tools

Neo4j
TigerGraph
LangChain
OpenAI

Job description

Tech Mirrors is hiring a Rules Engine Engineer to design and build a next-gen rule engine platform onsite in Iselin, NJ. The role focuses on integrating Gen AI for dynamic rule generation, leveraging graph data and data science models to detect patterns, and building robust APIs for enterprise integration.

The ideal candidate will have experience with rule engines, Gen AI frameworks, Python/Java, and graph databases, contributing to scalable, explainable AI-driven decisions.

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