Compose red-team / blue-team agentic workflows for production use-cases
Configure harnesses for cloud defense, vulnerability scanning, dynamic red-teaming, and penetration testing scenarios
Work directly on client use-cases, translating security requirements into agentic solutions
Turn prototype agents into deployed services that clients rely on
Design and implement context engineering that enables agents to operate effectively in cybersecurity domains
Orchestrate multi-agent systems for complex security workflows
Build the agentic layer that sits between the harness and the client
Ship fast and iterate based on client feedback and real-world performance
Operate independently while leveraging internal building blocks and frameworks
Collaborate with pentesters to ensure domain accuracy and effectiveness
Partner with SWE-Cyber to ensure the platform supports your use-case requirements

Strong applied AI engineer with hands-on experience building agents, LLM orchestration, context engineering, evals, and RAG systems
You ship fast, with a bias toward action and delivery
Operate independently with a customer-led mindset
Able to reuse internal components and bricks effectively
Some cyber context is a real plus, but not mandatory
we can pair you with pentesters for domain depth
Strong problem-solving abilities and attention to detail
Excellent communication skills and collaborative attitude
Genuine cyber or pentest knowledge
Experience building agentic harnesses or multi-agent systems end-to-end
Strong background in evals and benchmarking of agent systems
Experience with security tooling or workflows
Prior work on production AI systems in regulated or high-stakes environments

Applied AI Engineer, CyberSecurity

Key skills