AI Product Engineer, Abnormal Security

• 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
• 6+ 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

Desirable

• 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