Role overview
AI Engineer builds production AI systems for customer-facing products and the daily work of Engineering, Sales, Support, and Operations. Working on a small team with broad ownership, you will take ideas through prototypes and production in days or weeks, choosing projects by measurable impact. The product environment centers on developer APIs for authentication, identity, authorization, and secure access for people and agents.
Production AI and Developer Workflows
- Create customer-facing AI experiences, including an AI answer service, support bots in customer Slack channels, and new product interfaces.
- Build dependable internal agents, automations, and workflows with clear observability and maintainable services.
- Develop shared capabilities such as a unified bot framework, a sandboxed coding agent, and infrastructure that helps teams ship AI applications.
- Connect LLMs, embeddings, retrieval, and tool calling to documentation, Slack, GitHub, CRM, analytics, support systems, and internal services.
- Replace repetitive, multistep processes with coordinated AI workflows spanning applications and data sources.
- Evaluate new models and tools through focused experiments, then establish reusable patterns, libraries, and infrastructure.
Potential projects range from a coding sandbox that turns a bug report or feature specification into a deployed change to a shared, observable foundation for internal and customer-facing bots. Other examples include sales intelligence built from CRM, product usage, and conversation history; agents that combine ticket, Slack, and documentation workflows for triage and routing; and infrastructure that lets teams launch reliable AI tools without rebuilding the stack.
Experience for the Role
- Experience taking an AI system from idea to production and through at least one improvement cycle with real users.
- Strong engineering fundamentals and the ability to own services, data flows, and integrations from end to end.
- Experience developing with LLM APIs.
- Attention to failure modes, observability, and ongoing ownership beyond a successful demonstration.
- A practical focus on removing bottlenecks, saving time, and making new workflows possible.
- Comfort working through ambiguity and rapid changes in models, tools, problems, and implementation patterns.
Helpful Additional Experience
- Customer-facing AI products.
- Embeddings, retrieval and RAG architectures, structured tool calling, or agents.
- MCP or similar protocols that connect AI agents to operational systems.
Remote Work and Compensation
This is a full-time remote position open in the United States and Canada. US annual base salary is USD $175,000–$275,000, with equity and benefits separate. The range spans multiple levels; final compensation considers experience, skills, qualifications, and location. Compensation outside the United States is adjusted to local market benchmarks.
Benefits and Hiring
US benefits include:
- A matching 401(k) and equity.
- Medical, dental, and vision coverage for employees and families, an FSA, short- and long-term disability, and voluntary life insurance.
- Carrot fertility benefits.
- Twenty paid vacation days, ten holidays, and unlimited sick leave.
- Twelve weeks of fully paid parental leave.
- Monthly fitness and wellness stipends for activities such as gym memberships, yoga, races, massage, meditation, and therapy.
- Commuter benefits for employees choosing hybrid arrangements in San Francisco or New York City.
- Unlimited token usage.
Candidates outside the United States can discuss available benefits with recruiting. Hiring is inclusive and provides equal opportunity. AI may assist with application, resume, or response review, while people make final hiring decisions. Candidates can request information about how their data is processed.