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Fruition Executive Search

Software Engineer

Posted 9 Days Ago
In-Office
San Francisco, CA, USA
Entry level
In-Office
San Francisco, CA, USA
Entry level
Build and own full-stack AI systems for hospitality, including response generation, retrieval, tool orchestration, evaluation, observability, no-code controls, voice capabilities, infrastructure, data pipelines, and integrations. The role focuses on making AI agents reliable in real-world conversations with messy data and failing third-party APIs while optimizing performance and cost.
The summary above was generated by AI

The build: Our client is building full-stack AI systems for hospitality operations and guest communication. As an engineer on a small team with end-to-end product ownership, you'll own retrieval, tool orchestration, response generation, and production reliability — from the model-routing layer down to the infra.

This is an agent-reliability role: real conversations, messy data, third-party APIs that fail mid-flow. You make it work anyway.

What you'll do

  • Design and build the response generation pipeline — routers, orchestrators, synthesizers that classify intent, assemble context, select tools, and decide whether to send or escalate.
  • Develop knowledge retrieval that grounds responses in accurate, complete, current data despite messy inputs.
  • Build tool orchestration layers that execute multi-step workflows reliably, with graceful handling of API failures mid-conversation.
  • Create evaluation frameworks that measure quality against real conversations and catch regressions pre-customer.
  • Implement observability and tracing that makes agent reasoning legible to non-technical support teams.
  • Design no-code controls that let support leads adjust agent behavior.
  • Extend the system to voice — real-time transcription and the same tool-use capabilities as text.
  • Optimize speed and cost via model routing, caching, and prompt refinement.
  • Own infra, data pipelines, integrations, and API work.


Requirements

What we're looking for

  • Proven track record shipping production systems real users depend on.
  • Full-stack comfort — you pick up whatever the problem requires.
  • Deep thinking about reliable retrieval pipelines.
  • Pragmatism about models: frontier, fine-tuned, or simpler — whatever fits.
  • Strong eval discipline; you measure impact on real conversations before shipping.
  • Experience where your work directly shapes the product


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