Applied AI Engineer
Build and own customer-facing AI products from experimentation through production, including reliable agents, evaluation systems, APIs, interfaces, and infrastructure. Requires at least four years of software development experience and deep production experience with language-model systems.
About the job
Responsibilities
- Design and ship customer-facing AI experiences, from agent orchestration and tool use to supporting interfaces and backend systems.
- Build reliable agent loops that reason over complex context, call tools, recover from failures, and complete long-running tasks.
- Create evaluations, analyze failures, and improve prompts, context, models, tools, and product flows.
- Build APIs, data pipelines, interfaces, and production infrastructure to turn prototypes into polished products.
- Own complex AI products from experimentation through production.
- Help define technical direction and improve AI product quality and engineering practices.
- Collaborate 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 the ability to define solutions independently.
- Interest in engaging directly with customers.
- Experience mentoring other engineers.
Compensation & Benefits
- 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.
- Free transportation to and from work.
- Free lunch and dinner.
- Annual team offsite.
Skills
Python, Language Models, Agent Loops, Tool Use, Retrieval, Prompting, Structured Outputs, Frontend, Backend, APIs, Databases, Data Pipelines, Infrastructure, Evals, Production Systems
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