Lead Engineer (Breach & Attack Simulation)

Do you have a passion for understanding how AI systems are attacked? How about engineering a production platform that safely, repeatedly and measurably executes those attacks so customers can identify vulnerabilities and build defenses? If yes, APPLY NOW!

This Jobot Job is hosted by: Craig Rosecrans
Are you a fit? Easy Apply now by clicking the "Quick Apply" button and sending us your resume.
Salary: $250,000 - $400,000 per year

A bit about us:

We are partnering with a rapidly growing, well-funded AI cybersecurity company that is building technology designed to protect the AI systems, applications, models, and autonomous agents increasingly being deployed across the enterprise and government.

Following a major new round of funding, the company is expanding its approximately 30-person engineering organization and rethinking how products are built. Rather than large teams executing against predefined tickets, engineering is moving toward small, highly empowered three-person pods that own problems from customer discovery through architecture, development, validation, and production delivery.

We are searching for an exceptional Lead Engineer for the company's AI Attack Simulation platform.

Don't let the "Lead" title undersell the opportunity. This is essentially a Staff/Principal-level hands-on engineering role for someone who can combine deep software engineering ability with an attacker's mindset.

The central question behind the product is simple:

How would an attacker compromise this AI system—and how can we safely, repeatedly, and measurably reproduce those attacks before a real adversary does?

You'll help answer that question in production.

Why join us?

The company operates at the convergence of two of the most consequential technology categories today: artificial intelligence and cybersecurity.

Its broader platform helps organizations discover and understand the AI systems operating throughout their environments, protect AI applications at runtime, secure LLM/chatbot and agent workflows, simulate attacks against AI systems, monitor emerging coding-agent activity, and understand compliance with organizational and government security requirements.

Following a significant new funding round, the company is entering its next stage of growth while intentionally keeping engineering teams small and highly empowered.

This is an opportunity to join while many of the architectural, product, and engineering decisions are still being made—and have meaningful influence over them.

Compensation: $250K–$350K base salary + meaningful equity

Location: Fully Remote – U.S

Job Details

What You'll Build

You'll take substantial technical ownership of an AI Attack Simulation platform designed to help customers identify vulnerabilities across AI models, applications, LLM-powered systems, and emerging agentic workflows.

This isn't a traditional penetration-testing position, and it isn't simply another LLM application development role.

You'll be responsible for helping productize offensive security techniques—turning attacks, adversarial behaviors, and security-testing methodologies into scalable software that customers can continuously use to understand and improve the security posture of their AI environments.

Depending on your background, that could include areas such as:

AI red teaming and automated attack simulation
Adversary emulation and breach & attack simulation
Adversarial machine learning
LLM and AI application security testing
Prompt injection, jailbreaks, model manipulation, and emerging AI attack techniques
Autonomous or agentic offensive-security workflows
Continuous security validation
Automated penetration-testing concepts
Attack orchestration and execution
Detection, measurement, and analysis of attack outcomes
What Makes This Role Different

Engineering is intentionally being pushed much closer to the customer and the actual problem being solved.

You'll work within a small, autonomous engineering pod, partnering closely with the individual responsible for stewarding the product. Engineers aren't expected to simply receive requirements from Product and disappear into a backlog.

You'll help:

Speak directly with customers and understand their security problems
Determine what should actually be built
Prototype and validate ideas quickly
Make architectural and technical decisions without excessive bureaucracy
Build production-quality systems
Analyze product and customer-usage data
Validate solutions with customers
Iterate rapidly based on what you learn

The company wants engineers who are comfortable operating with speed, ambiguity, autonomy, and accountability.

You won't always have perfect information. The strongest engineers here are able to absorb context, make a thoughtful decision, execute, learn, and adjust rather than waiting for every variable to be resolved.

The Technical Environment

The broader engineering environment includes technologies such as:

Go | Python | Redis | OpenSearch | Kubernetes | AWS | Microservices | AI/LLM Systems | Agentic AI

Exact language alignment is less important than engineering depth.

If you've spent your career building sophisticated systems in another modern language but have deep offensive-security knowledge and can quickly become productive in Go/Python environments, we still want to talk.

The Profile We're Looking For

The ideal candidate sits somewhere at the intersection of:

Offensive Security × Production Software Engineering × AI/ML Security × Agentic Systems × Product Engineering

You may currently be a:

Staff Software Engineer
Principal Software Engineer
Lead Engineer
Security Research Engineer
Offensive Security Engineer
AI Security Engineer
Adversarial ML Engineer
Red Team Engineer
Security Product Engineer
Founding Engineer

We're especially interested in engineers who have built products involving AI red teaming, breach & attack simulation, adversary emulation, automated penetration testing, continuous security validation, autonomous security agents, or AI/ML security.

What We're NOT Looking For

This distinction is important.

We're not searching for a traditional penetration tester whose experience stops at identifying vulnerabilities and writing reports.

We're also not searching for an AI researcher whose primary output has been papers, experiments, or notebooks.

And simply building an LLM-powered application isn't enough.

We need someone who understands how sophisticated attacks work and has the software engineering ability to turn those concepts into reliable, scalable, production-grade technology.

You need to be a builder.

You'll Likely Thrive Here If You...
Naturally think about systems from an attacker's perspective
Have deep production software engineering experience
Have worked with offensive-security, adversary-emulation, attack-simulation, or AI-security concepts
Are actively experimenting with or building agentic/LLM systems
Can move comfortably between architecture and hands-on implementation
Enjoy owning ambiguous technical problems rather than waiting for detailed specifications
Can make sound technical decisions quickly
Want direct exposure to customers and product strategy
Prefer small, high-output engineering teams over layers of process
Can operate effectively in a rapidly evolving startup environment

Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.

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