Data Engineer - GenAI

Reply•Detroit, MI

1d•$90,000 - $110,000

About The Position

Concept Reply, part of the Reply Network, is a leader in IoT solutions. We support and advise our customers in Automotive, Manufacturing, Smart Infrastructure and beyond in all aspects of Internet of Things (IoT) and Cloud Computing. From designing and developing customized IoT solutions to implementing and managing them seamlessly, Concept Reply helps customers unlock the potential of IoT. We are seeking a Data Engineer to join our team and contribute to the development of data-driven and generative AI solutions, working directly with clients as part of a consulting engagement. The ideal candidate has a strong foundation in data engineering and graph databases, hands-on experience with GenAI and RAG (Retrieval-Augmented Generation) architectures — GraphRAG in particular — is comfortable working client-facing, and has a passion for data and AI.

Requirements

Bachelor's degree
Must be a U.S. citizen or Green Card holder
At least 3 years of professional experience in data engineering or a related technical field
Experience with Python
Experience with AWS or Azure cloud platforms
Experience developing ETL pipelines and familiarity with ETL frameworks
Experience with Databricks and/or Snowflake
Experience with graph databases (e.g. Neo4j)
Hands-on experience with GenAI/LLM projects, including RAG and GraphRAG
Direct client-facing experience

Nice To Haves

Background in consulting or professional services
Experience with DevOps and CI/CD pipeline development
Experience with AI/ML-driven applications

Responsibilities

Design, build, and maintain data pipelines and ETL workflows
Build and maintain graph database models supporting downstream applications
Design and implement RAG/GraphRAG pipelines to power generative AI applications on top of graph and data platforms
Work closely with data engineers and scientists to build and enhance data and AI-driven solutions
Engage directly with client stakeholders — gathering requirements, presenting progress, and translating business needs into technical solutions
Collaborate with a small cross-functional delivery team