IFD AI Engineer

Chipply

33d

About The Position

Chipply is seeking an Internal Forward Deployed AI Engineer to embed with internal teams and develop AI-powered solutions. This role focuses on reducing manual work, accelerating decision-making, and improving company-wide productivity. The engineer will build production-grade solutions such as agents, integrations, and deterministic tooling by leveraging APIs, webhooks, and MCP surfaces of existing systems like HubSpot, Microsoft 365, Confluence, and Slack. The position requires the ability to discern when AI is the appropriate tool versus a deterministic solution. This is an evolving role where the engineer will define work, reshape priorities, and build capabilities from scratch, reporting directly to the CEO. Collaboration with leadership and various departments (Engineering, Finance, Sales, Marketing, Customer Support, Product) is key to identifying and implementing high-impact opportunities.

Requirements

Five to eight years of professional software engineering experience, with significant time spent shipping production code against third-party APIs and SaaS platforms.
Strong programming fundamentals in at least one modern language for AI and integration (Python and TypeScript preferred).
Comfortable writing, testing, deploying, and operating code in production.
Hands-on experience building against the APIs of business SaaS platforms (e.g., HubSpot, Microsoft Graph/Microsoft 365, Slack, Confluence).
Demonstrated experience building with large language models in production (prompt and context design, tool use/function calling, retrieval, evaluation, cost/latency tradeoffs).
Hands-on experience with AI agent frameworks and MCP connectors, or comparable multi-step automation spanning multiple systems.
Practical experience building with a major LLM provider (Claude, OpenAI, Gemini, Copilot, or similar).
Familiarity with business process automation tools (e.g., HubSpot workflows, Zapier, Make.com, n8n).
Strong problem-solving and debugging skills, with the ability to diagnose issues across distributed systems.
Excellent project management skills, with the ability to balance multiple priorities and meet deadlines.
Self-starter comfortable with ambiguity and thriving in fast-moving environments.
Strong cross-functional communication skills, able to translate technical capabilities into business outcomes and business problems into technical specs.
Curiosity and discipline to stay current on the AI landscape and translate trends into practical applications.
Excellent interpersonal and collaboration skills, with strong organizational habits and attention to detail.
Ability to maintain confidentiality and exercise discretion when handling sensitive data.
Bachelor's degree in computer science, information systems, or a related field is preferred but not required; equivalent professional engineering experience is welcome.

Nice To Haves

Knowledge of security best practices for API integrations, secrets management, and AI system data handling.

Responsibilities

Design, build, and maintain AI agents, integrations, and automations to reduce manual work, eliminate bottlenecks, and improve productivity.
Inspect internal SaaS platforms (HubSpot, Microsoft 365, Confluence, Slack, etc.) to understand their APIs, webhooks, and MCP connectors, and use these to build necessary integrations.
Partner with leadership and department heads to identify and prioritize high-impact opportunities by mapping workflows and pinpointing areas for engineering improvement.
Write production code, build multi-tool and multi-agent systems connecting internal platforms, and make judgment calls on AI vs. deterministic solutions.
Build evaluations and monitoring for AI systems to ensure measurable output quality.
Act as Chipply's internal AI champion, leading education, training, and adoption efforts, and serving as the go-to engineering resource for AI.
Establish and maintain responsible AI governance, including guidelines for data handling, privacy, model selection, output quality monitoring, and ethical use.
Continuously evaluate emerging AI tools, agent frameworks, model providers, and orchestration libraries, piloting promising technologies.
Measure and report on the ROI of shipped systems, tracking time saved, error reduction, cost impact, and quality improvements.
Develop and maintain documentation for systems, integrations, and AI workflows.
Serve as a liaison across departments to align on technology needs and ship workflow improvements.
Monitor security and compliance across integrations and AI systems, collaborating to ensure data protection best practices.
Continuously redefine the scope, priorities, and deliverables of the role based on evolving company needs and the AI ecosystem.