Fullstory

Technology

SeniorDataPipeline&AIEngineer

$155–215k ~AI est. Atlanta, Georgia, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Data Pipeline & AI Engineer at Fullstory. Skills: Data pipelines, AI integration, Cloud data warehouses. Maintain Go microservices. Extend Go microservices”

What You'll Achieve.

Ship improvements to pipeline; Increase throughput; Reduce latency; Improve data quality; Establish evaluation criteria; Establish tooling for LLM outputs; Measure AI quality; Improve AI quality; Shape AI agent platform direction; Lead initiatives

Industry & Context.

Technology
Problems you'll solve

Owning large technical problems; Troubleshooting production incidents

What They're Looking For.

Must Have

Significant experience building and operating high-throughput data pipelines, Work with cloud data warehouses like BigQuery, Snowflake, or Databricks, Proficiency in Go, Python, Java or a similar language, Hands-on experience with data transformation tooling such as dbt, Understanding of data modeling, Understanding of pipeline observability, Familiarity with LLM integration patterns, Familiarity with LLM evaluation approaches, Track record of owning major system areas end-to-end, Driving architectural decisions, Maintaining production health, Improving reliability over time, Reside within commutable distance to Atlanta office

Nice to Have

Experience with LangSmith, Experience with Vertex AI, Demonstrated ability to ramp quickly in applied AI

What You'll Do.

Maintain Go microservices

Extend Go microservices

Scale Go microservices

Transform session data

Enable AI agent integrations

Orchestrate pipelines

Ensure data migrations

Define evaluation frameworks

Ensure AI agents produce accurate results

Investigate production incidents

Resolve production incidents

Implement systemic fixes

Write technical design documents

Drive consensus on architectural changes

Surface scaling bottlenecks

Surface cross-team dependencies

Demonstrate technical judgment

De-risk work through spikes

How You'll Work.

Team & Collaboration

Product engineers; ML engineers

Communication Scope

Technical design documents

Full Job Description

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. Fullstory Anywhere is one of Fullstory's three primary product verticals, and it's growing fast. We put Fullstory's rich digital experience data directly into customers' hands: in their warehouses, in their AI workflows, and in the tools their teams already use. As our Senior Data Engineer, you will report to the Senior Engineering Manager for the Fullstory Anywhere team and help build the systems that transform, move, and activate billions of data points at massive scale so that customers can unlock insights in their own environments and build intelligent agents on top of real user behavior. You will design and optimize pipelines that process 30 billion+ records per day across customer warehouses, collaborate with product and ML engineers to define how LLM-powered customer agents evaluate and act on Fullstory data, and make architectural decisions that balance throughput, cost, and reliability across a product vertical with accelerating revenue and adoption. To excel in this job, you must be comfortable owning large, ambiguous technical problems end-to-end, from initial design through production health, and know how to build data-intensive systems that stay reliable as they scale. In a typical day, you might: - Maintain, extend, and scale Go microservices that transform and deliver Fullstory session data into customer warehouses and power the team's MCP server that enables AI agent integrations. - Develop and maintain dbt models and pipeline orchestration to ensure timely, fault-tolerant data migrations across hundreds of customer destinations. - Define evaluation frameworks for LLM outputs using tools like Langsmith and Vertex AI, ensuring AI-powered customer agents produce accurate, useful results. - Investigate and resolve production incidents across the data pipeline, implementing systemic fixes t

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