AI Automation Engineer

Fullstory•Atlanta, GA

2d•Hybrid

About The Position

This is a hybrid position requiring in-office attendance one day per week at our Atlanta office. Candidates must reside within a commutable distance to be considered. The AI Automation Engineer will report to the Director, Engineering (Enterprise Systems and Data team) and help the Finance team leverage AI so that they can enhance data analysis, automate key workflows, and make more effective business decisions. You will work embedded within the Finance team to identify opportunities for AI solutions and act as the technical bridge between them and other engineering groups. To excel in this job, you must have a tenacious problem-solving mindset and enjoy building the "glue" that connects systems to enable new capabilities.

Requirements

Experience working closely with business stakeholders, preferably within a finance or business operations context.
Proven experience designing and building solutions by integrating various systems (e.g., REST APIs, databases), with a strong comfort level in managing the associated data flows.
Strong programming skills for tasks like data acquisition, cleaning, and preparation.
Experience with data warehousing (e.g., BigQuery, Snowflake) and a solid understanding of data modeling.
Bachelor's Degree in Computer Science or related field.

Nice To Haves

Candidates must reside within a commutable distance to be considered.
You will be proactively identifying new, complex business problems to solve with AI and scaling your solutions, potentially with other teams.
You will be contributing to broader engineering discussions about AI best practices and helping to shape the future of AI automation at Fullstory.

Responsibilities

Work embedded within the Finance team to identify opportunities and implement AI-powered solutions to complex business problems.
Guide and empower finance professionals to effectively use AI tools and technologies for data analysis and decision-making.
Design, build, and maintain the technical infrastructure required to enable AI, including custom tools, server-side logic, system integrations, and data pipelines.
Develop and manage data acquisition processes, including sourcing, cleaning, and preparing data for use in AI models and analytics.
Conduct data analysis to uncover insights, validate data integrity, and support strategic finance initiatives.
Act as the technical bridge between the Finance team and other engineering groups, translating business needs into robust technical solutions.
Improve team productivity through the identification and implementation of AI solutions that automate or optimize key workflows for the Finance team.