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Ciridae

End-to-end AI transformation and deployment

Forward Deployed Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • Production software shipped end-to-end across the stack, including React and TypeScript on the frontend, Python on the backend, and APIs in use.
  • Experience building RAG systems, agents, and evaluations.
  • Ability to turn incomplete requirements and evolving user feedback into working software.
  • Ability to communicate with both CFO and CTO audiences.
  • Comfort working with ambiguity.
  • Willingness to spend meaningful time with customers and take responsibility for system adoption and intended outcomes.

Responsibilities

  • Own the full solution end-to-end, from an ambiguous operational problem through architecture, frontend, backend, data, integrations, LLM orchestration, production cutover, and success metrics.
  • Own deployment and oversee integrations.
  • Build production-grade working demos and carry systems from initial build through real-world use.
  • Write React, shape Postgres schemas, and debug agent loops.
  • Feed field learnings back into Crucible as reusable tooling, patterns, and platform capabilities.
  • Lead engagements from start to finish for experienced Forward Deployed Engineers.

About the Company

Ciridae

End-to-end AI transformation and deployment

Ciridae provides end-to-end AI transformation services that help organizations become AI-first. It combines strategy with hands-on implementation to identify high-impact opportunities, modernize data foundations, and deploy production-grade AI systems that automate workflows across business functions. Its process includes diligence and risk assessment, workflow redesign, full-stack system construction (with integrations to existing systems), and ongoing command-and-control operations to monitor performance, handle exceptions, and iterate in production. Ciridae sits between traditional consulting and engineering teams, offering quick initial solutions and scalable architectures for longer-term transformation, especially in environments with legacy processes. The goal is to enable enterprises and PE-backed operators to adopt AI at scale, improve efficiency through automation, and maintain reliable, governed AI systems over time.

Company size
11-50
Company stage
Seed
Total funding
$20M
Headquarters
San Francisco, CA
Founded
2025

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