Staff Software Engineer - GenAI Innovations

Abnormal Security
Remote - USAPosted 30 March 2026

Job Description

About the Role Enterprises of all sizes trust Abnormal AI to stop cybercrime. We believe that to stay ahead of attackers, we must fundamentally rebuild our RD organization to be AI-Native . We are moving toward a future where AI-initiated workflows—where agents write the first draft of designs, code, and remediation—are the standard. As we scale these agentic workflows, we require a new class of infrastructure designed for autonomous execution. As an Engineer on the AI Accelerator team, you will act as both a technical owner and a force multiplier. You will architect the developer tooling and platform infrastructure that enables hundreds of engineers (and thousands of agents) to build software faster than ever. You will be expected to build and ship critical AI DevX systems while also influencing Abnormal’s broader AI strategy. You are building the "Operating System" for our engineering team—removing the structural bottlenecks that separate human intent from shipped code for mission-critical systems. About You You are a High-Slope Builder. You don't wait for a roadmap. You thrive in the terminal, instinctively crafting reusable tools as you work. You prioritize "unblocking" and velocity, but you never sacrifice quality—you use AI to ship better code, faster. You are a Product Engineer for Developers. You are obsessed with your "customers". You don't build technology for technology's sake; you build tools that solve genuine pain points and delight the engineers who use them daily. You possess Engineering Breadth. You are a true generalist when wielding AI tools. You are comfortable jumping between architecting cloud infrastructure, writing backend services in Python/Go, and "vibe coding" a frontend dashboard to visualize the data. You are an "AI-Native" Engineer. You don't just use AI; you have integrated it into your core workflow to operate with 10x leverage. What You Will Do Architect the "Agent-Ready" infrastructure, building the sandboxed environments and headless interfaces that allow AI agents to execute safely without human hand-holding Embed with product teams to identify friction in the "Plan → Code → Test" loop, shipping 0-to-1 internal tools that ruthlessly automate bottlenecks Replace manual human validation with deterministic proof; you will build the validation frameworks that allow agents to verify their own work Act as a technical scout for the organization, critically evaluating emerging agentic frameworks to inform our build-vs-buy strategy Must Haves Typically 4+ years of professional software engineering experience Deep familiarity with modern AI coding workflows (Cursor, Claude Code) and the ability to engineer around model limitations You are focused on solving user problems and shipping solutions that get adopted, not just building infrastructure in a vacuum Uncompromising focus on velocity x excellence; you instinctively write scripts to automate tasks, but ensure they are robust enough for production use Demonstrated ability to navigate ambiguity and ship complex features with minimal oversight Nice to Haves Production-grade systems expertise spanning Backend services (Python/Go), Cloud Infrastructure, and Data Systems Experience with or interest in AI evangelism—sharing knowledge through documentation, workshops, or technical sessions Experience building internal developer platforms, CLIs, or CI/CD systems at scale History of contributing to open source developer tools or AI frameworks #LI-ML1 Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location. In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package. Base salary range: $210,400 $302,500 USD Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, reli ... (truncated, view full listing at source)
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