
AI Engineer
San Francisco, CAFull-timeSeen 1w agoStill listed 4 days ago
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At a glance
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Job overview
Stacksync is building a deterministic AI execution platform for mission-critical enterprise operations. The AI Engineer will build production-grade agents for structured process execution and implement guardrails and evaluation suites, including schema enforcement and human-in-the-loop fallback triggers. The role suits a systems-minded full-stack engineer who values transactional guarantees, operational ownership, and solving backend, distributed queue, and non-deterministic agent challenges.
Skills & qualifications
Skills
Full job description
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
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Deterministic Execution Engines: Build production-grade AI agents designed for structured process execution rather than open-ended chat loops.
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Guardrails & Evaluation Suites: Implement programmatic guardrails, schema enforcement, human-in-the-loop fallback triggers This Role IS for You If
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You understand why enterprise AI requires strict guardrails, transactional guarantees, and deterministic process execution over unconstrained agents.
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You are a systems-minded full-stack engineer who loves tackling difficult backend, distributed queue, and non-deterministic agent problems.
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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
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You think building enterprise AI is just writing prompts or making simple calls to OpenAI/Anthropic APIs.
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You dislike operational complexity or debugging non-deterministic failure modes and state drift.
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You require long, slow timelines or highly structured corporate environments. Tech Stack & Tooling Languages & Frameworks: Python, React, Postgres ⚠️ Apply By Answering ⚠️
- What excites you about building guardrailed, process-executing AI execution engines over open-ended chat assistants? (2–3 sentences max)
- What is the most technically complex agent workflow, guardrail system, or real-time distributed pipeline you've built? Highlight how you handled state, failure modes, or verification loops.
How this job compares
Set against the 7,472 open AI Engineer jobs on Olive Jobs, counted November 7, 2026.
- Pay
- This postingNot listed
- California median$156–261K/yr1,178 salary ranges
- US median$31–80/hr118 hourly ranges
- Openings
- Olive Jobs lists 1,444 open AI Engineer jobs in California and 7,472 across the US. 9% of them nationwide are listed as remote or flexible.
- Hiring the most in California
- Deloitte184 open
- Accenture97 open
- Capital One60 open
- Experience
- This posting asks for at least 3 years of experience — less than three in four AI Engineer postings that state a minimum ask for (median 5 years, across 6,440 postings).
- Education
- 2,867 of the 7,472 open AI Engineer jobs (38%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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