aimlroles

Applied AI Engineer

WorkOS workos.com Open · verified Oct 22, 2026
Remote San Francisco Full-time Mid-level AI Engineering

At a glance

Mid-level AI Engineering role at WorkOS. Remote, United States · full-time · $175,000–$275,000 base.

SalaryStated by WorkOS
$175,000 – $275,000
Base salary for this role, in USD per year, as published in the posting.
This role, from WorkOSOur estimate for the market: $183,750–$246,250Median $215,000
The range includes the market median of $215,000 for mid-level AI engineering roles in San Francisco, compared against the San Francisco market.
Worked out from 47 postings that stated pay, median $215,000. Last updated Oct 21, 2026.
RoleAI Engineering
SeniorityMid-level
LocationSan Francisco
WorkplaceRemote
EmploymentFull-time
Base pay$175,000–$275,000
PostedFeb 27, 2026 · 7mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build AI products for customers, including support bots in Slack and new customer-facing tools
  • Create dependable internal agents and workflows that people can use in their daily work
  • Connect language models, retrieval and tool use with company documents, Slack, GitHub and business systems
  • Turn manual work across apps and data sources into coordinated AI workflows
  • Test new models and tools, then help establish reusable engineering patterns and infrastructure

What you bring

  • You have taken AI systems from an initial idea into production and improved them using feedback from real users
  • You can own services, data flows and integrations end to end, with strong engineering fundamentals
  • You have built software using LLM APIs

Who this fits

This mid-level role suits an engineer who likes turning operational bottlenecks into working AI systems and is comfortable defining approaches as the tools and problems change. You’ll work across internal teams and customer-facing products in a remote role based in San Francisco.

From the employer

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) 💖

At WorkOS, we offer resources that emphasize personal and familial well-being. We offer healthcare coverage for you and your family, including medical, dental, and vision. We offer parental leave, paid-time off and fully remote working arrangements.

  • 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.