AI Software Engineer

ONETRACK.AI•Chicago, IL

1d•$160,000 - $250,000•Remote

About The Position

OneTrack is a profitable, growth-stage technology company redefining manufacturing and logistics with physical AI. OneTrack operates as the intelligence layer for physical operations. We serve the world's largest brands and logistics companies by deploying camera sensors and other data-capture devices alongside our mission control platform and AI agents. Today, OneTrack runs in hundreds of warehouses and factories across North America with companies like Ashley Furniture, Mars Snacking, The Wonderful Company, Ryder, and Church & Dwight. We're hiring a full-stack engineer to join our team and work on AiOn, our agentic AI platform. The scope covers the whole product: the UI operators use, the agent and prompt design behind it, the Python services, and the AWS infrastructure they run on. From floor-level to supervisors to C-suite executives at Fortune 500s, our agentic AI platform connects the systems of record with places of action in some of the most demanding operational environments. AiOn is already live in hundreds of warehouses and factories, so the work splits roughly evenly between new features and making what exists faster, more reliable, and more extensible. We integrate frontier models from multiple providers rather than train our own, so the engineering is in the product around them. We work from first principles and ship the simplest thing that solves the problem, then refine it.

Requirements

5+ years building production full-stack or backend software, or a track record demonstrating equivalent depth
Recent hands-on experience integrating LLMs into user-facing production applications
Shipped a user-facing agentic or LLM-powered feature and owned it across the full stack
Built evaluation harnesses for non-deterministic systems
Track record of improving reliability, performance, and maintainability of production systems
Strong Python and TypeScript/React, both used daily
Built agent orchestration, or deep experience with a framework and its tradeoffs
REST API and service design, plus async and event-driven patterns (queues, streaming, WebSockets)
Production experience deploying and running services on AWS
Product judgment for user-facing AI, including iterating from operator feedback and handling uncertain output well
Fluent with agentic coding tools (Claude Code, Codex, Cursor, or similar)

Nice To Haves

Tool and system integration for agents (e.g. MCP)
Sandboxing and safe execution of untrusted code
LLMOps or AgentOps tooling and CI/CD for AI systems
Streaming and WebSocket patterns for real-time or long-running tasks
Data-ingestion pipelines and multi-store data consistency
Logistics, supply chain, or physical-operations domain experience

Responsibilities

Ship and evolve full-stack features from UI through API to agent logic
Build and extend our agent framework: tool and function calling, multi-step reasoning, and context management
Build structured tool and data access over operational data with schema grounding, validation, and safe execution, and integrate the external systems agents act on
Build evaluation and observability for quality, latency, safety, cost, and product outcomes such as task completion
Improve reliability, robustness, and latency across a distributed, event-driven backend, and re-architect early implementations as the platform matures
Maintain guardrails: least-privilege tool design, safe execution boundaries, fallbacks, and kill switches
Work anywhere in the stack the problem requires: React and TypeScript UI, an Electron desktop app, streaming interfaces that stay usable while output is still partial, and Python services on AWS built around async and event-driven patterns