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MintlifyMintlify

Senior Applied AI Engineer

Build and lead production AI products, including agent systems that use tools, retrieve context, and complete complex tasks reliably. The role requires strong full-stack engineering, deep language-model experience, product judgment, and ownership from experimentation through production.

About the job

Responsibilities

  • Architect and ship customer-facing AI experiences, including agent orchestration, tool use, user interfaces, and backend systems.
  • Develop reliable agent loops that reason over complex context, call tools, recover from failures, and complete long-running tasks.
  • Define evaluations, build feedback loops, analyze failures, and systematically improve prompts, context, models, tools, and product flows.
  • Turn prototypes into reliable production systems by making decisions about architecture, latency, cost, observability, and user experience.
  • Shape product direction and engineering approaches across the stack.
  • Own complex AI products from experimentation through production.
  • Talk directly with customers and use their insights to shape products.
  • Mentor engineers, share technical knowledge, and help teammates grow.

Requirements

  • At least 4 years of professional software development experience.
  • Deep experience building production systems with language models, including agent loops, tool use, retrieval, prompting, and structured outputs.
  • Experience owning production software across frontend, backend, APIs, databases, and infrastructure.
  • Experience leading complex projects from experimentation through production.
  • Strong product intuition and interest in building user-facing software.

Benefits and Compensation

  • Competitive compensation and equity.
  • 20 days of paid time off annually.
  • 401(k) or RRSP.
  • $420/month wellness stipend.
  • 100% coverage for health, dental, and vision insurance.
  • Free rides to and from work.
  • Free lunch and dinner.
  • Annual team offsite.

Skills

Python, Language Models, AI Agents, Agent Orchestration, Tool Use, Retrieval, Prompt Engineering, Structured Outputs, Frontend Development, Backend Development, APIs, Databases, Infrastructure, Observability, Evaluation Systems