Applied AI Engineer

About the role

We're growing our Applied AI team to dramatically increase productivity across Engineering, Sales, Support, and Operations, and to ship AI-powered products that customers rely on directly. As an Applied AI Engineer, you'll design and ship production AI systems that change how WorkOS builds, sells, supports, and scales. You’ll also be building things that WorkOS customers use, and systems that the entire company depends on daily.

Responsibilities

• Design and ship customer-facing AI products like ask.workos.com, AI support bots embedded in customer Slack channels, and new surfaces we haven't built yet
• Build internal tools that become part of people's daily work: agents, automations, and workflows that are stable, observable, and easy to maintain
• Work on big bets: a unified bot framework, a sandboxed coding harness agent, and infrastructure that lets the entire company ship
• Use LLMs, embeddings, retrieval, and tool-calling to plug into docs, Slack, GitHub, CRM, analytics, support systems, and internal services
• Replace repetitive, multi-step manual processes with orchestrated, AI-driven flows that span multiple apps and data sources
• Stay current on new models and tooling, run focused experiments, and help the team converge on patterns, libraries, and infrastructure that compound over time

Requirements

• You've taken AI-powered systems from idea to production and through at least one iteration cycle with real users
• Strong engineering fundamentals. You're comfortable owning services, data flows, and integrations end-to-end
• Experience building with LLM APIs
• You think about failure modes, observability, and ownership, not just whether the demo works
• Bias toward action. You care less about the model and more about removing real bottlenecks, saving hours, or unlocking workflows the company couldn't do before
• Bias toward action. You care less about the model and more about removing real bottlenecks, saving hours, or unlocking workflows the company couldn't do before
• Comfort with ambiguity and fast change. The problem, the tools, and the "right" patterns are all evolving, you're excited to help define them

Qualifications

• Prior work on customer-facing AI products
• Experience with embeddings, retrieval/RAG architectures, and structured tool-calling or agents
• Exposure to MCP or similar protocols for connecting AI agents to real systems

Skills

• Strong engineering fundamentals
• Experience building with LLM APIs
• Experience with embeddings, retrieval/RAG architectures, and structured tool-calling or agents
• Exposure to MCP or similar protocols for connecting AI agents to real systems

Benefits

• Competitive pay
• Substantial equity grants
• Healthcare coverage for you and your family, including medical, dental, and vision
• Parental leave, paid-time off, and fully remote working arrangements
• Wellness and fitness monthly allowances
• PTO + paid holidays + unlimited sick leave
• Unlimited token usage

Pay

$175K - $275K

Schedule

Full-time