Product Engineer, AI
Fluidstack6 hours ago
Base Salary
$224k - $300k/yr
Responsibilities
- Build software for recruiting, interviewer capacity, hiring workflows, and onboarding.
- Develop cash forecasting, purchase-order and contract-based payment schedules, and capital deployment tracking.
- Automate financing proof chains and connect funding releases to verified construction milestones.
- Extract obligations, pricing, deadlines, penalties, and SLAs from contracts and change orders.
- Embed with finance, treasury, accounting, legal, recruiting, and delivery teams to convert expert workflows into structured data and generated work.
- Design, implement, and ship production features autonomously from problem identification through adoption.
Requirements
- Production experience with Go, Python, or TypeScript and the ability to learn additional languages as needed.
- Experience building production features with OpenAI, Anthropic, or open-weight model APIs, MCP servers, and agentic frameworks.
- Daily experience using AI coding tools such as Claude Code and Cursor.
- Ability to work autonomously, move quickly under deadlines, and build foundations other engineers can extend.
- Experience earning credibility with non-engineering experts and driving software adoption in real operational workflows.
- Strong product judgment and ability to create intuitive interfaces that match users’ real work.
- Preferred experience with ERP and fixed asset accounting, FP&A, cash forecasting, capital planning, structured finance, treasury operations, contract lifecycle systems, ATS or HRIS integrations, or LLM extraction from legal and financial documents.
Benefits
- Competitive total compensation package including cash and equity.
- Health, dental, and vision insurance.
- Retirement plan.
- Generous paid time off policy.
Tech Stack
Categories
AI ApplicationsProduct Engineering
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.