aitypescriptsaasgraphqlreactlanggraphmcpnodepostgresqlmulti agent systems
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Вышеразвернуть
$200к-300к/год
$140к$170кмедиана$210к
По похожим ролям (27) ~ $170к/год
На СНГ рынке: $4.2к/мес ($3.6к - $5к)
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Крутая вакансия
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Вы будете отвечать за архитектуру производственного AI-продукта в прибыльной растущей софтверной компании, с понятной зоной ответственности и заметным влиянием на технические решения; фокус на индустрии каннабиса сужает сферу применения опыта.
Выше рынка
Современный стек
Заметное влияние
Фокус на AI
?Узкая отрасль
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Staff AI Product Engineer (Agentic AI): Architecting and building production multi-agent systems, MCP integrations, unified data layers, contextual memory systems, and evaluation suites for an enterprise AI platform with an accent on reliability, observability, safe workflow execution, and customer data. Focus on designing the agentic stack, shipping production tools, setting architectural standards, and rapidly experimenting with emerging models and frameworks.
Location: Remote, Worldwide; fully remote across 4 continents
Salary: USD 200,000–300,000 per year
Company
hirify.global provides ERP and B2B eCommerce software for the cannabis industry, processing inventory, manufacturing, sales, and logistics operations, and is building an AI infrastructure platform for commercial businesses.
What you will do
Architect and build a production multi-agent system that safely operates across ERP, CRM, spreadsheets, calendars, email, analytics, and compliance systems.
Build and maintain MCP integrations connecting hirify.global with Claude, Codex, and external AI harnesses.
Develop a unified data layer and contextual memory system that ingests customer data, creates profiles, and improves agent experiences.
Own reliability, observability, durable execution, permissions, safe workflow execution, and production rollback processes.
Create evaluation suites from real customer use cases and set standards for building, testing, and shipping agents.
Prototype emerging agentic frameworks, models, toolkits, and coding workflows, collaborating with product, engineering, leadership, and customers.
Requirements
7+ years of full-stack development experience, ideally building B2B SaaS applications.
Production experience building multi-agent harnesses and MCPs, beyond prototypes or personal projects.
Strong understanding of reliability, observability, permissions, safe workflow execution, and production systems.
Experience operating across product and engineering, including scoping, roadmap influence, and technical decision-making.
Proficiency in React, TypeScript, Node, PostgreSQL, GraphQL, and LangGraph, with the ability to learn new tools and frameworks quickly.
Experience at an early-stage startup with fewer than 20 engineers, including setting direction in ambiguity.
Daily AI tool use with tool, workflow, and build fluency: creating agents or workflows, writing evals, selecting code versus models appropriately, and deploying guarded, observable systems to real users.
Team-first behavior, clear communication, proactive risk identification, and solution-oriented collaboration.
Nice to have
Experience building supply chain, ERP, CRM, B2B marketplace, or accounting software.
UX design experience.
Additional agentic systems experience, including evaluation frameworks or agent-to-agent protocols.
Experience using Claude Code or similar tools to build products independently.
Cannabis industry experience.
Culture & Benefits
Remote work across 4 continents, with benefits varying by country and employment type.
18 days of PTO plus 11 holidays; sick days do not count toward PTO.
Medical, dental, vision, and 401(k) benefits for US employees.
Employee-friendly option terms, including a 10-year exercise window after two years if leaving.
Access to advanced AI tools, an AI stipend, AI classes and workshops, demo days, hackathons, and yearly in-person team offsites.
Direct customer and go-to-market collaboration in a culture focused on experimentation, product taste, and mutual respect.
Hiring process
Answer three written application questions about building with LLMs.
Complete a recruiter screen, technical interview with a live harness design discussion and workflow walkthrough, and a 3–4-hour harness take-home covering product, UX, system design, and implementation.
Review the take-home with two engineers, followed by references and an offer.
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