{"id":3369107,"url":"https://alion.io/job/stacksync-ai-engineer","title":"AI Engineer","company":{"id":6588,"name":"Stacksync","domain":"stacksync.com","url":"https://alion.io/company/stacksync","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Work at a Startup","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":147000,"max_usd":284000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"Claude Code","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI","optional":false},{"name":"PostgreSQL","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-10-28T00:19:09Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-28T09:49:39Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Build the deterministic AI execution layer for enterprise operations\n> 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.\nEnterprise 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.\nOur 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.\nWhat You Will Work On in Your First 90 Days\n- Deterministic Execution Engines: Build production-grade AI agents designed for structured process execution rather than open-ended chat loops.\n- Guardrails & Evaluation Suites: Implement programmatic guardrails, schema enforcement, human-in-the-loop fallback triggers\nThis Role IS for You If\n- You understand why enterprise AI requires strict guardrails, transactional guarantees, and deterministic process execution over unconstrained agents.\n- You are a systems-minded full-stack engineer who loves tackling difficult backend, distributed queue, and non-deterministic agent problems.\n- You think like a product owner, take end-to-end ownership, and thrive in fast-moving startup environments.\nThis Role IS NOT for You If\n- You think building enterprise AI is just writing prompts or making simple calls to OpenAI/Anthropic APIs.\n- You dislike operational complexity or debugging non-deterministic failure modes and state drift.\n- You require long, slow timelines or highly structured corporate environments.\nTech Stack & Tooling\nLanguages & Frameworks: Python, React, Postgres\nApply By Answering\n1. What excites you about building guardrailed, process-executing AI execution engines over open-ended chat assistants? (2-3 sentences max)\n2. What is the most technically complex agent workflow, guardrail system, or real-time distributed pipeline you've built? 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