Job Overview
Location
San Francisco, CA
Job Type
Full-time
Category
Software Engineering
Date Posted
June 13, 2026
Full Job Description
đź“‹ Description
- • Build core software primitives end to end, focusing on entity ownership, audit trails, authorization, and orchestration to ensure the right actions are default and the wrong ones are structurally difficult.
- • Own and evolve Fluidstack’s domain model, translating real-world infrastructure elements—power, data centers, and chips—into durable, composable software entities that remain scalable and maintainable over years.
- • Design and implement systems that interface with external vendor formats including KMZ, BIM, Revit, and unstructured technical documentation to ingest and operationalize domain-specific data.
- • Develop an AI agent platform that enables AI to act as first-class operators within infrastructure workflows, equipped with real authorization controls, audit trails, and guardrails—moving beyond advisory roles to autonomous execution.
- • Construct a live, self-updating model of AI infrastructure project schedules that replaces static Gantt charts with dynamic, reality-responsive workflows that auto-adjust as conditions change across teams.
- • Automate the generation of end-to-end data center site designs by processing thousands of pages of unstructured vendor materials against internal DC design standards.
- • Write production-grade code in any language using AI-assisted coding tools, ensuring systems are reliable, observable, and depended on by other teams.
- • Leverage AI tooling daily, including LLM APIs, MCP servers, and agentic frameworks, with proficiency in tools like Claude Code or Cursor to accelerate development.
- • Turn messy, unstructured data into structured, usable systems through experience in machine learning, data engineering, or research contexts.
- • Apply rigorous domain modeling informed by past failures, identifying and eliminating janky one-offs by extracting the single underlying primitive that unifies multiple systems.
- • Learn rapidly in unfamiliar domains—whether authz models, geospatial formats, or workflow engines—and achieve competence faster than traditional expertise allows.
- • Contribute to building civilization-scale infrastructure for AI by operating at the frontier of compute deployment, with high ownership, autonomy, and velocity across hardware and software layers.
🎯 Requirements
- • Move toward ambiguity, not away from it; build clarity and maps in uncertain domains
- • Learn rapidly in unfamiliar technical domains, achieving competence faster than traditional expertise allows
- • Have taste in abstraction: identify underlying primitives and know when not to over-abstract
- • Have shipped production code that others depend on, using AI-assisted coding tools in any language
- • Be fluent with AI tooling: LLM APIs, MCP servers, agentic frameworks, and daily use of tools like Claude Code or Cursor
- • Have experience turning messy, unstructured data into usable systems via ML, data engineering, or research
🏖️ Benefits
- • Competitive total compensation package including salary and equity
- • Retirement or pension plan aligned with local norms
- • Health, dental, and vision insurance
- • Generous PTO policy aligned with local norms
Skills & Technologies
About FluidStack Inc.
FluidStack Inc. operates a distributed cloud platform that aggregates under-utilized GPUs in data centers and individual machines worldwide, renting them on-demand to AI researchers, startups, and enterprises for training and inference workloads. The company automates deployment, security, and billing, offering prices up to 80% below traditional hyperscalers while providing instant access to high-end NVIDIA A100, H100, and consumer GPUs through a single API and web console. Headquartered in London, FluidStack targets machine-learning engineers who need scalable, low-cost compute without long-term commitments, claiming thousands of active nodes and customers including Fortune 500 enterprises and leading research labs.
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