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# Software AI Engineer

- **Company:** AutoStore
- **Location:** Atlanta, GA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Machine Learning, Retrieval-Augmented Generation, Large Language Models, Information Technology, Low Latency, Virtual Agents
- **Published:** September 3, 2026
- **Apply:** https://autostore.wd3.myworkdayjobs.com/autostore/job/Atlanta-GA-USA/Software-AI-Engineer_JR102673

## About the Role

* 3-5 years building and deploying ML or AI systems in production, not just research or prototyping.
 * Bachelor's degree in Computer Science, Engineering, or a related field required; Master's preferred.
 * Hands-on experience with LLM agent development: retrieval-augmented generation, tool and API integration, and multi-step orchestration frameworks.
 * Experience deploying and operating models on cloud infrastructure, with a working understanding of cost, latency, and scaling tradeoffs.
 * Applied background with optimization and/or ML algorithms on hard problems (routing, scheduling, coordination, or comparable).
 * Time-series modeling and forecasting experience (anomaly detection, predictive analytics on sensor or telemetry data).
 * Prior work in hard-tech or physical-systems environments where models run against real hardware and reliability constraints (preferred).
 * Effective in distributed teams across time zones.

## Description

AutoStore is hiring an AI Engineer to support our rapidly growing Engineering team. In this role, you'll work cross-functionally to enable engineering groups to build AI capabilities into their products while serving as a subject matter expert to internal teams. If you have a background in ML engineering in a scaled environment, we want to hear from you.

Key Tasks and Responsibilities:

 * Build and ship AI agent systems that connect to data sources and tools, including retrieval, API integration, and multi-step orchestration.
 * Deploy and operate AI on cloud infrastructure, tuning the cost, performance, and scaling tradeoffs for production workloads.
 * Apply optimization and ML algorithms to hard operational domains such as robot fleet routing and coordination.
 * Build time-series models and forecasting for operational telemetry, including anomaly detection and predictive analytics on sensor and equipment data.
 * Deliver against physical systems with real reliability constraints, where model outputs drive or inform hardware behavior.


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