Staff AI Product Engineer

Accountabilities

• Lead the architecture, design, and development of a production-grade multi-agent system capable of safely executing actions across core business tools, including ERP, CRM, spreadsheets, calendars, email, analytics, and compliance platforms.
• Own the development and continuous improvement of Model Context Protocol (MCP) integrations that connect internal business systems with external AI environments and assistants.
• Design and implement a unified data infrastructure that consolidates information from multiple sources into a centralized layer accessible to AI agents and external tools.
• Build contextual memory and customer profiling systems that ingest business data and enable increasingly personalized, intelligent AI experiences.
• Establish robust reliability, observability, permission management, and durable execution mechanisms to ensure agents operate safely on real customer data.
• Develop and maintain comprehensive evaluation frameworks and automated tests based on real-world customer use cases to measure agent performance and prevent regressions.
• Define architectural standards, engineering patterns, and best practices for building, testing, deploying, and maintaining agentic systems across the engineering organization.
• Stay ahead of developments in AI models, agentic frameworks, orchestration tools, and emerging technologies, incorporating valuable innovations into the product architecture.
• Rapidly prototype new AI capabilities and present technical concepts and product opportunities to internal teams and customers.
• Work hands-on with AI-assisted development tools such as Claude Code, continuously improving personal engineering workflows and sharing effective practices with the wider team.
• Collaborate closely with engineering leadership, product teams, and customers to shape the AI roadmap, prioritize initiatives, and translate business challenges into impactful technical solutions.
• Provide technical mentorship and influence engineering direction while maintaining a strong focus on execution, product quality, and measurable customer outcomes.

Requirements

• At least 7 years of full-stack software development experience, ideally building and scaling B2B SaaS applications.
• Proven, hands-on experience designing and deploying production-grade multi-agent systems, beyond experimental prototypes or personal projects.
• Demonstrated experience building and maintaining MCP servers or integrations used in production environments.
• Strong understanding of production engineering principles, including system reliability, observability, security, permissions, and safe workflow execution.
• Experience combining product thinking with technical leadership, including defining scope, making architectural decisions, and influencing product roadmaps rather than focusing exclusively on implementation.
• Proficiency in React, TypeScript, Node.js, PostgreSQL, GraphQL, and LangGraph, with the ability to quickly learn and adopt new technologies and frameworks.
• Previous experience in an early-stage startup environment, preferably within an engineering team of fewer than 20 people, with a track record of taking ownership and setting direction in ambiguous situations.
• Strong practical AI fluency, including daily use of Claude Code or comparable AI development tools, and the ability to build custom agents, skills, and automated workflows.
• Ability to design and implement effective AI evaluation processes, understand when to use language models versus conventional code, and build appropriate safeguards around AI-generated actions.
• Experience deploying AI agents to real users with suitable guardrails, monitoring, observability, and rollback mechanisms.
• Strong product and engineering judgment, with the ability to distinguish high-value opportunities from unnecessary complexity and deliver intuitive AI-powered experiences.
• Excellent communication skills, with the confidence to raise concerns, propose solutions proactively, and communicate complex technical concepts clearly.
• Collaborative, low-ego mindset, prioritizing team success, product quality, and shipped outcomes over internal politics or individual recognition.

Additional Advantages

• Experience with supply chain software, ERP, CRM, B2B marketplaces, or accounting platforms.
• UX design capabilities.
• Advanced agentic systems, evaluation frameworks, or agent-to-agent protocols.
• Independent product development using AI coding tools.
• Familiarity with the cannabis industry.