AI Product Engineer

Abnormal Security is building AI-native systems that transform how enterprise GTM teams operate — and we're doing it by shipping real products on a weekly cadence. 

The AI Transformation Engineering team is the infrastructure layer that makes this possible: we build and maintain the platforms, integrations, and tooling that power a growing fleet of AI agents operating across Sales, Customer Success, and Marketing.

As an AI Product Engineer, you'll work at the intersection of platform engineering and direct product delivery. Some weeks you're extending agent infrastructure — building new tools, connectors, and APIs that let AI agents do things they couldn't do before. Other weeks you're shipping GTM tooling directly, moving fast because the shortest path to impact is writing the code yourself. 

You'll collaborate closely with AI Product Managers who define and build automations weekly, unblocking them with new platform capabilities and partnering on what to build next.

This is a high-visibility, high-autonomy role. You'll demo your work every Friday. Your systems will be used by a 700-person GTM org. You'll work closely with engineering and product leadership and have line-of-sight to the CEO’s priorities.

• Build and extend agent platform capabilities — new tools, APIs, data connectors, and integrations that expand what AI agents can do without manual intervention
• Ship self-serviceable GTM tooling that enables non-technical users to set up their own AI-initiated LLM workflows.
• Partner with AI Product Managers on platform requirements — translate their roadmap blockers into well-scoped engineering deliverables with reliable timelines
• Identify and build reusable infrastructure — proactively design horizontal capabilities that accelerate multiple product workstreams at once
• Own reliability and observability for the systems you build — you're not handing off to an ops team
• Demo your work weekly and communicate clearly to technical and non-technical stakeholders alike

You're an engineer who ships things. You've built LLMs and agents in production — not as a side experiment, but as the core of what you were delivering. You have strong product instincts alongside engineering depth: you ask "who is this for and what do they actually need?" before writing code. You move fast without being careless, and you use AI coding tools as force multipliers, not crutches.

You're motivated by ownership and velocity. You'd rather have a small surface area and full accountability than a large team and a ticket queue.

• 2+ years of software engineering experience (strong internship and project portfolios considered)
• Demonstrated experience building with LLMs, agents, or AI APIs in a real product context — show us something that shipped
• Proficiency in Python; comfort picking up new frameworks quickly
• Experience integrating external APIs and building data pipelines
• Strong written communication — you can write a clear spec and a clear async update
• Ability to work with high autonomy, minimal oversight, and surface blockers proactively

• Frontend or full-stack experience (React/Next.js) for building internal tools and dashboards
• Familiarity with agentic frameworks (LangGraph, CrewAI, Autogen) or production-scale prompt engineering
• Prior experience in a startup or high-velocity small team
• Open source contributions or a public portfolio of AI projects

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