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Chipply

IFD AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listedRemote

About the Job

Requirements

  • Five to eight years of professional software engineering experience, including meaningful experience shipping production code against third-party APIs and SaaS platforms.
  • Strong programming fundamentals in at least one modern language used for AI and integration work; Python and TypeScript are preferred. Ability to write, test, deploy, and operate production code.
  • Hands-on experience building against business SaaS APIs such as HubSpot, Microsoft Graph/Microsoft 365, Slack, or Confluence, or comparable platforms, including reading API documentation, evaluating authentication and rate-limit constraints, and designing robust integrations.
  • Demonstrated experience building with large language models in production, including prompt and context design, tool use/function calling, retrieval, evaluation, and cost and latency tradeoffs.
  • Hands-on experience with AI agent frameworks and Model Context Protocol connectors, or comparable multi-step automation spanning multiple systems; ability to explain when an agent architecture is appropriate versus a deterministic pipeline.
  • Practical experience building with a major large language model provider such as Claude, OpenAI, Gemini, or Copilot; production-grade platform experience is acceptable.
  • Familiarity with business process automation tools such as HubSpot workflows, Zapier, Make.com, or n8n, sufficient to determine when off-the-shelf automation is preferable to new code.
  • Problem-solving and debugging ability to diagnose issues across distributed systems and design iterative, scalable solutions.
  • Project management ability to balance multiple priorities, meet deadlines, and deliver continuous improvements while maintaining quality.
  • Comfort working independently amid ambiguity and a rapidly evolving role scope.
  • Ability to translate technical capabilities into business outcomes for non-technical stakeholders and business problems into technical specifications.
  • Ability to maintain confidentiality and exercise discretion when handling sensitive company and customer data.
  • A bachelor's degree in computer science, information systems, or a related field is preferred but not required; equivalent professional engineering experience is welcome.

Responsibilities

  • Design, build, and maintain AI agents, integrations, and automations that reduce manual work, remove bottlenecks, and improve productivity across departments.
  • Inspect internal SaaS platforms, including HubSpot, Microsoft 365, Confluence, and Slack, to identify available APIs, webhooks, and Model Context Protocol connectors, then build the integrations teams need.
  • Partner with leadership and department heads to identify and prioritize high-impact opportunities by mapping workflows and identifying where AI-powered or deterministic engineering can deliver measurable improvement.
  • Write production code and build multi-tool and multi-agent systems connecting internal platforms into end-to-end processes; determine when AI or deterministic solutions are appropriate.
  • Build evaluations and monitoring for deployed AI systems so output quality can be measured.
  • Lead internal AI education, training, and adoption efforts, and serve as an engineering resource for AI questions, best practices, and emerging use cases.
  • Establish and maintain responsible AI governance covering data handling, privacy, model and tool selection, output-quality monitoring, and ethical use.
  • Evaluate emerging AI tools, agent frameworks, model providers, and orchestration libraries; pilot promising technologies and recommend adoption based on impact, cost, and fit.
  • Measure and report the return on investment of deployed 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 Engineering, Finance, Sales, Marketing, Customer Support, and Product to align on technology needs and deliver workflow improvements end to end.
  • Monitor security and compliance across integrations and AI systems, collaborating with engineering and leadership to follow data-protection best practices.
  • Continuously redefine the role's scope, priorities, and deliverables as company needs and the AI ecosystem evolve.

Desired Qualifications

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

About the Company

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Milwaukee, WI
Founded
2015

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