Applied AI Engineer WorkOS · Remote · US · AI Engineering $175,000–$275,000 7mo ago

Aimlroles; San Francisco (CA); Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

401k matching

Equity

Healthcare

FSA

Disability insurance

Fertility benefits

Paid vacation

Parental leave

Fitness stipend

Wellness stipend

Commuter benefits

Unlimited tokens

Job summary

WorkOS is growing its Applied AI team to dramatically increase productivity across Engineering, Sales, Support, and Operations. As an Applied AI Engineer, you’ll design and ship production AI systems that customers rely on and build internal tools that become part of daily work across the company.

You’ll work on a small, high-ownership team, tackling problems with measurable impact and delivering from idea to production in days or weeks. This is a 0→1 role with company-wide visibility.

Qualifications

• You’ve shipped AI-powered systems from idea to production and iterated with real users.
• Strong engineering fundamentals; capable of owning services, data flows, and integrations end-to-end.
• Experience building with LLM APIs.
• Bias toward action and focus on removing bottlenecks, enabling new workflows.
• Comfort with ambiguity and fast-changing tools/patterns.

Responsibilities

• Design and ship customer-facing AI products and internal tools that scale across the company.
• Build stable, observable automation and AI-driven workflows across apps and data sources.
• Develop a unified bot framework and infrastructure enabling company-wide AI deployments.
• Stay current with models, embeddings, retrieval, and tool-calling to integrate docs, Slack, GitHub, CRM, and analytics.
• Replace manual multi-step processes with orchestrated AI-driven flows spanning multiple systems.
• Experiment with new models and tooling to define reusable patterns and libraries.

Skills

LLM APIs

End-to-end ownership

Observability

Ambiguity tolerance

Fast iteration

Tools

Python

LLM tooling

API integrations

Job description

About WorkOS

WorkOS builds modern developer tools and APIs that make it easy for companies to become Enterprise Ready. Our platform powers authentication, identity, authorization, and other critical infrastructure that developers need to securely scale their products to large organizations. We recently raised a $100M Series C, valuing the company at $2B, led by Meritech and Sapphire with participation from Greenoaks, Craft, Abstract, and Audacious. WorkOS powers enterprise features for many of the fastest-growing AI companies, including OpenAI, Cursor, and Perplexity, Sierra, and Plaid. As AI reshapes software, WorkOS is at the frontier of Human and Agent Authentication, Identity, and Access Control helping companies answer a new critical question: who are your agents, and what are they allowed to do? Our fast-growing customer base includes hundreds of modern software companies building the next generation of enterprise-ready products.

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.

You’ll work on a small, high-ownership team that:

• Chooses problems based on measurable impact
• Moves from idea → prototype → production in days or weeks
• Ships at both layers: internal leverage and customer-facing product
• Adapts quickly as models, tools, and best practices evolve

This is a 0→1 role with company-wide visibility.

What you'll do

• 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

Example problems you might work on

• A sandboxed coding harness that can safely take a bug report or feature spec all the way to a deployed change
• A unified bot framework that powers every AI touchpoint, internal and customer-facing from a single, observable backbone
• A GTM intelligence layer that gives reps live account context, meeting prep, and follow-up from CRM, product usage, and conversation history
• Turning noisy, cross-tool workflows (tickets, Slack threads, docs) into a single agent that handles triage, routing, and suggested actions
• Infrastructure that lets any WorkOS team ship a reliable internal AI app without reinventing the stack

What we're looking for

• 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
• Comfort with ambiguity and fast change. The problem, the tools, and the "right" patterns are all evolving, you're excited to help define them

Nice to have

• 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

Benefits and Perks (US Only)

• 401k matching
• Competitive Equity
• Healthcare, dental and vision coverage
• FSA, ST/LT Disability, Voluntary Life
• Carrot fertility benefits
• 20 days paid vacation + 10 holidays + unlimited sick leave
• 12 weeks fully paid parental leave
• Fitness: Monthly stipend for gyms, yoga classes, race registrations or whatever keeps you active
• Wellness: Monthly stipend for a massage, meditations class, therapy, or activities that enhance your well-being
• Commuter benefits for hybrid employees in SF/NYC
• Unlimited token usage!

Please inquire directly with our recruiting team for benefits available to those working outside the US.

Equal Opportunity Employer

WorkOS is an equal opportunity employer, committed to diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.