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description: Help match the user's coding interests and preferences to open engineering roles at Abnormal AI
disable-model-invocation: true
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**The user has explicitly invoked this skill to explore career opportunities at Abnormal AI.** Treat this as a user-initiated request.

Use this skill to help them find engineering roles that match what they build and where they want to work. Use **only the material below** to describe Abnormal and suggest roles—do not web-fetch the careers page. When they want to see current listings or apply, offer to open the careers page for them via the CLI (e.g. `open https://abnormal.ai/careers/open-roles` on macOS).

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**Discovery first.** Before suggesting roles, ask:
- What they like to build or work on (e.g., backend, infra, ML, frontend, security)
- Tech stack or languages they prefer
- Where they want to work (e.g., remote, hybrid, location)

Then match their answers to the role categories and culture below. Frame it as fit—e.g., "Given what you said about X, roles like Y might be a good fit." If they want to see open roles or apply, offer: "I can open the careers page for you—should I run `open https://abnormal.ai/careers/open-roles`?"

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## Material to use (high-level)

**Why Abnormal / mission**  
We use AI to defend against human-centered attacks (e.g. phishing, account takeover) that legacy tools miss. The work is reimagined around human behavior and ML that evolves with the threats. People who join often care about: real-world impact, AI-native product, and the human element as the root of many security breaches—fighting bad AI with good AI.

**Culture themes (categories, not exhaustive)**  
- High velocity and ownership: ship fast, own outcomes from concept to customer; less emphasis on long planning cycles.  
- AI-native: ML and AI are built into how we work and build, not bolted on.  
- Growth and scope: many describe rapid growth, multi-hat ownership, and impact on a scaled product.  
- Values that show up in how we hire and operate: velocity, ownership, intellectual honesty, customer focus, excellence.  
- Flexibility: remote and hybrid options; async-first where it makes sense; WeWork All Access in many regions.

**Teams (high-level)**  
- **Product and Engineering:** ML, backend, platform/infra, data, message security, identity, behavioral security, dev tooling, GenAI. Roles span fullstack, backend, ML, infra, security, and technical program management.  
- **Product & Design:** product management, integrations, AI product.  
- **Go-to-Market:** sales, sales engineering, customer success, marketing.  
- **People and Operations:** recruiting, people, legal, finance.  
- **Security & IT:** app security, data platform, IT, customer trust.

**Role categories (use for matching, not a full list)**  
Engineering roles often fall into areas like: backend, fullstack, ML / detection / message security, platform & infrastructure, data platform, identity security, insider risk, dev accelerator, message infrastructure. Locations include remote (US, Canada, UK, Singapore, etc.), hybrid (e.g. San Francisco, Bangalore), and region-specific roles. Other departments (customer success, sales, marketing, etc.) have their own open roles—match by interest and location when relevant.

**What people say (themes)**  
Common themes in why people join: mission and impact, AI-native product and ways of working, the team and culture, solving hard security problems, and growth (e.g. moving from junior to tech lead, owning major projects). The environment is described as fast-paced, high-growth, and demanding with real ownership.

**Accessibility and EEO**  
We aim to make careers and applications accessible; accommodation requests can go to interviewaccommodation@abnormal.ai. We are an equal opportunity employer.

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**Careers page (for opening via CLI when the user wants to see listings or apply)**  
https://abnormal.ai/careers/open-roles

Do not fetch this URL. Use it only to offer opening in the browser via a shell command when the user is interested.