Founding AI/ML Engineer | Live Product, Equity & Growth

Xuman.AI

San Francisco (CA)

On-site

USD 180,000 - 240,000

Full time

10 days ago
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Benefits offered by this job

Equity stake
Early-stage cash compensation
Milestone-based growth

Job summary

Xuman.AI is building the Human Experience Engine and is hiring for a role governing the agentic layer of our live product. You will design, run, and rebuild the multi-agent system, including tool calling, orchestration, guardrails, and voice on LiveKit, with real users interacting with each agent.

You will own model strategy and costs, and shape the data/ML foundation, collaborating with two AI engineers to ship production-ready AI experiences at scale in a rapidly evolving startup environment.

Qualifications

  • 5+ years of real AI/ML work with agentic LLM products shipped to users.
  • A model you trained or fine-tuned and production-ready with hand-built evals.
  • Multi-agent orchestration with failure paths and architecture changes.
  • Python in production and comfort with a TypeScript service (NestJS gateway).
  • Daily use of AI tools (Claude, Copilot, ChatGPT) to write, debug, and ship faster.

Responsibilities

  • Own the agentic layer in production: agents, tool calling, orchestration, guardrails, voice on LiveKit.
  • Define model strategy and model cost: what we run, where, at what price.
  • Own the data and ML foundation, collaborating with two AI engineers.

Skills

AI/ML experience
Agentic LLM products shipped
Python production
TypeScript
Multi-agent orchestration
Model evaluation

Tools

NestJS

Job description

Xuman.AI is building the Human Experience Engine and is hiring for a role governing the agentic layer of our live product. You will design, run, and rebuild the multi-agent system, including tool calling, orchestration, guardrails, and voice on LiveKit, with real users interacting with each agent.

You will own model strategy and costs, and shape the data/ML foundation, collaborating with two AI engineers to ship production-ready AI experiences at scale in a rapidly evolving startup environment.

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