Decision Engineer, Manufacturing & Supply Chain
Fluidstack3 months ago
Austin, TX, USA +3 moreMid Level
H1B sponsor
Base Salary
$224k - $300k/yr
Responsibilities
- Build decision systems and internal tools using frontier models to improve manufacturing and supply chain productivity.
- Own tools end to end from conception through production, iterating with the people who use them.
- Design and maintain shared AI infrastructure, including AGENTS.md, SKILLS.md, and organizational skills.
- Build custom integrations between LLMs and Slack, GitHub, internal APIs, and operational data.
- Monitor evolving AI capabilities and identify opportunities to apply emerging techniques.
Requirements
- At least 3 years of software engineering experience writing production-grade code in Go, Python, and TypeScript, with the ability to work in arbitrary languages.
- Strong full-stack development skills building web applications with React, Next.js, or similar frameworks.
- Hands-on experience building applications with OpenAI, Anthropic, or open-weight model APIs, creating and using MCP servers, and working with agentic frameworks.
- Daily demonstrable use of AI coding agents such as Claude Code or Cursor, including concrete examples of tools and skills built.
- Ability to identify problems, design solutions, and ship high-impact results autonomously with minimal direction.
- Strong product and systems judgment, comfort with ambiguity, and ability to work at a demanding pace.
- Excellent communication skills, including translating technical concepts for non-technical stakeholders and driving adoption.
- Exposure to manufacturing, supply chain, logistics operations, or internal tooling for operational teams is preferred.
Benefits
- Competitive total compensation package including cash and equity.
- Health, dental, and vision insurance.
- Retirement plan.
- Generous paid time off policy.
Tech Stack
Categories
About Fluidstack
Fluidstack provides on-demand GPU cloud infrastructure for AI training and inference, offering dedicated clusters of NVIDIA H200 and GB200 systems. The company sells compute capacity and managed clusters to AI labs, enterprises, and public-sector teams that need high-throughput workloads. Founded in 2017 and headquartered in New York, it is privately held.