AI Engineer

Moonfire; San Francisco (CA); On-site; USD 138,000 - 220,000; Full time

Job summary

Moonfire's Stacksync team in San Francisco is hiring an AI Engineer to architect the deterministic AI execution layer for enterprise operations. You will build production-grade agents that execute structured business processes with guarantees.

You'll own backend challenges across distributed queues and state management, implement guardrails and evaluation suites, and collaborate with product and data teams in a fast-paced startup environment.

Qualifications

• 3+ years of experience in engineering, backend focus.
• Experience building scalable backend systems and distributed architectures.
• Understanding of enterprise software and deterministic execution concepts.

Responsibilities

• Build production-grade AI agents for structured process execution.
• Implement guardrails, schema enforcement, and human-in-the-loop triggers.

Skills

Backend engineering

Distributed systems

System design

End-to-end ownership

Tools

Python

React

PostgreSQL

Job description

Stacksync

Real-time and two-way sync between CRMs and Databases

AI Engineer

$100 - $160

0.07%

San Francisco, CA, US

Job type Full-time

Role Engineering, Backend

Experience 3+ years

Visa Will sponsor

About the role

Build the deterministic AI execution layer for enterprise operations

> Our Thesis: While consumer AI tools and coding assistants (like Claude Code) focus on unconstrained, single-user tasks, mission-critical enterprise operations require a fundamentally different architecture. Enterprise adoption cannot rely on free-roaming personal agents. It demands deterministic execution engines, robust operational guardrails, automated verification loops, and bulletproof process orchestration.

Enterprise software integrations are still painfully fragile: workflows break silently, APIs fail unpredictably, systems drift out of sync, and teams waste countless hours maintaining infrastructure never built for real-time operations at scale.

Our platform powers operations for supply chains, logistics, healthcare, financial operations, e-commerce, and enterprise sales. When our systems run, AI agents execute business processes deterministically: orders move, invoices sync, warehouses operate, contracts renew, revenue gets recognized, and critical workflows execute in real time.

What You Will Work On in Your First 90 Days

- Deterministic Execution Engines: Build production-grade AI agents designed for structured process execution rather than open-ended chat loops.

- Guardrails & Evaluation Suites: Implement programmatic guardrails, schema enforcement, human-in-the-loop fallback triggers

This Role IS for You If

- You understand why enterprise AI requires strict guardrails, transactional guarantees, and deterministic process execution over unconstrained agents.

- You are a systems-minded full-stack engineer who loves tackling difficult backend, distributed queue, and non-deterministic agent problems.

- You think like a product owner, take end-to-end ownership, and thrive in fast-moving startup environments.

This Role IS NOT for You If

- You think building enterprise AI is just writing prompts or making simple calls to OpenAI/Anthropic APIs.

- You dislike operational complexity or debugging non-deterministic failure modes and state drift.

- You require long, slow timelines or highly structured corporate environments.

Tech Stack & Tooling

Languages & Frameworks: Python, React, Postgres

About the interview

• Meet with the CTO
• Real-world technical scenarios (not LeetCode)
• System design and architecture discussions
• Production/debugging-oriented conversations

About Stacksync

Stacksync powers real-time and two-way data synchronization between CRMs and Databases. Engineers and RevOps teams use Stacksync to (1) build backbone CRM integrations, (2) build internal tools on real-time customer data and (3) ship customer metrics from their database/data warehouse to their business teams.