Company Overview Chipply is the industry's preferred web store platform that gives the power to team dealers, custom apparel decorators, and corporate suppliers to launch online stores with confidence and grow their GMV efficiently. Primary Purpose and Function Chipply is hiring an Internal Forward Deployed AI Engineer to embed with our internal teams and ship AI-powered solutions that reduce manual work, accelerate decision making, and improve productivity across the company. This role reports to the CEO and is responsible for building real, production-grade engineering work — agents, integrations, and deterministic tooling — directly on top of the systems Chipply already runs on. This is a hands-on engineering role, not an orchestration or admin role. You will not be configuring SaaS platforms from the ground up. Instead, you will inspect the systems we already use (HubSpot, Microsoft 365, Confluence, Slack, and others), understand what APIs, webhooks, and MCP surfaces they expose, and partner with each department to design and build the AI agents, integrations, and automations that plug into them. Where AI is the right tool, you build with AI. Where a deterministic solution is better, you build that instead. The judgment to know the difference is part of the job. This is also an intentionally evolving role. The scope of AI in the business will change as tools, models, and capabilities mature, and you must be comfortable defining the work as you go, reshaping priorities frequently, and building capabilities from the ground up. You will report directly to the CEO and partner closely with leadership, Engineering, Finance, Sales, Marketing, Customer Support, and Product to identify high-impact opportunities and ship the engineering work that captures them. Responsibilities Design, build, and maintain AI agents, integrations, and automations that reduce manual work, eliminate bottlenecks, and improve productivity across every department at Chipply. Inspect Chipply's internal SaaS platforms (HubSpot, Microsoft 365, Confluence, Slack, and others) to understand what APIs, webhooks, and MCP connectors they expose, and use those surfaces to build the integrations each team needs. Partner with leadership and department heads to identify and prioritize high-impact opportunities by mapping existing workflows and pinpointing where engineering effort — AI-powered or deterministic — will deliver measurable improvement. Write production code. Build multi-tool and multi-agent systems that connect Chipply's internal platforms into seamless end-to-end processes. Make sound judgment calls on when AI is the right tool and when a deterministic solution is a better fit. Build evals and monitoring for AI systems you ship, so output quality is measurable rather than assumed. Serve as Chipply's internal AI champion by leading education, training, and adoption efforts, and by acting as the go-to engineering resource for AI questions, best practices, and emerging use cases. Establish and maintain responsible AI governance, including guidelines for data handling, privacy, model and tool selection, output quality monitoring, and ethical use. Continuously evaluate emerging AI tools, agent frameworks, model providers, and orchestration libraries; pilot promising technologies and recommend adoption decisions based on impact, cost, and fit. Measure and report on the ROI of the systems you ship, tracking time saved, error reduction, cost impact, and quality improvements. Develop and maintain documentation for the systems, integrations, and AI workflows you build so institutional knowledge scales with the company. Serve as a liaison across Engineering, Finance, Sales, Marketing, Customer Support, and Product to align on technology needs and ship workflow improvements end to end. Monitor security and compliance across the integrations and AI systems you build, collaborating with engineering and leadership to ensure data protection best practices are followed. Continuously redefine the scope, priorities, and deliverables of the role as Chipply's needs and the broader AI ecosystem evolve. Requirements Qualifications Five to eight years of professional software engineering experience, with a meaningful portion of that time spent shipping production code against third-party APIs and SaaS platforms. Strong programming fundamentals in at least one modern language commonly used for AI and integration work (Python and TypeScript preferred). Comfortable writing, testing, deploying, and operating code in production. Hands-on experience building against the APIs of business SaaS platforms — HubSpot, Microsoft Graph / Microsoft 365, Slack, Confluence, or comparable systems. You should be able to read API docs, evaluate auth and rate-limit constraints, and design a robust integration on top of them. Demonstrated experience building with large language models in production: prompt and context design, tool use / function calling, retrieval, evaluation, and cost and latency tradeoffs. Hands-on experience with AI agent frameworks and MCP (Model Context Protocol) connectors, or comparable multi-step automation that spans multiple systems. You should be able to explain when an agent is the right architecture and when a deterministic pipeline is better. Practical experience building with a major LLM provider (Claude, OpenAI, Gemini, Copilot, or similar). Chipply primarily uses Claude, but experience with any production-grade LLM platform is welcome. Familiarity with business process automation tools (HubSpot workflows, Zapier, Make.com, n8n) — not as your primary craft, but enough to know when an off-the-shelf automation is the right answer instead of new code. Strong problem-solving and debugging skills, with the ability to diagnose issues across distributed systems and design iterative, scalable solutions. Excellent project management skills, with the ability to balance multiple priorities, meet deadlines, and ship continuous improvements