GenAI Engineer

Insight Global
Dallas, United States of America
14 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Dallas, United States of America

Tech stack

API
Artificial Intelligence
Apache HTTP Server
Big Data
Information Engineering
Data Infrastructure
Decision Support Systems
Python
Snowflake
Backend
FastAPI
Data Analytics
Data Pipelines
Databricks
Microservices

Job description

Insight Global is looking for a skilled GenAI Engineer who is well versed in both development and data engineering. This role will focus on building a competitive intelligence platform, aggregating and analyzing both internal and external data to surface insights that influence the organization's pricing, marketing, and go-to-market decisions. The individual will design and develop scalable, backend services that integrate AI and generative AI capabilities to improve data-driven decision making. The ideal candidate is a strong Python developer with deep experience in data engineering and AI, working within a microservices architecture using FastAPI. The role is heavily backend-focused and requires hands-on experience with modern data platforms such as Databricks and Snowflake to enable large-scale analytics and intelligent insight generation.

Requirements

Extensive hands-on python development experience building backend services & data pipelines in production environments

-Deep background in data engineering & AI including hands-on experience integrating generative AI capabilities into data-driven platforms

-Hands-on experience with modern data platforms, specifically Databricks & Snowflake to support large-scale data processing and analytics

-Expertise in microservices architecture, including building and deploying APIs using FastAPI

-Experience working with internal and external data sources, aggregating and transforming data to produce actionable business insights (e.g., for pricing, marketing, or competitive intelligence) -Experience with Apache Iceberg for managing large-scale analytic datasets

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