Backend Senior Software Engineer, Attack and User Emulation Team (AUE)
$160,000–$225,000 year
RemoteUnited States
Job Summary
Architect and deliver highly scalable, fault-tolerant microservices for cybersecurity range simulations using Spring Boot, Kubernetes, and event-driven messaging. Design AI-enabled workflows and autonomous emulation behaviors by integrating Model Context Protocol and agent-to-agent communication patterns. Lead end-to-end execution of multi-quarter initiatives while mentoring engineers through design reviews and code quality standards. Establish robust observability frameworks to ensure high availability and zero-downtime deployments. Embed security and compliance directly into the software development lifecycle for offensive and defensive mitigation.
Required Qualifications
- 4+ years of hands-on software development experience with a track record of architecting, building, and operating large-scale, distributed microservices in production
- 2 year degree in science & technology or commensurate experience
- Deep Expertise in OOP languages such as Java or Kotlin, with proven experience in advanced API design, system integration, and event-driven architectures
- Production Expertise in container orchestration platforms (Kubernetes, Docker) and enterprise frameworks (Spring Boot)
- Experience integrating AI/LLM capabilities into production software systems, with sound judgment around service boundaries, context management, reliability, security, and observability
- Proven Track Record of leading complex, multi-system initiatives from ideation to delivery, making sound pragmatic trade-offs between speed, scalability, and technical debt
- Strong understanding of cybersecurity concepts, including offensive/defensive tactics, user emulation techniques, or threat landscapes
- Experience identifying system bottlenecks, improving fault tolerance, and resolving complex distributed systems failures
- In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire
Desired Qualifications
- Experience evaluating or integrating AI or machine learning capabilities into production backend systems, particularly when model-driven behavior must be reliable, observable, and safely controlled
- Exposure to Reinforcement Learning (RL) concepts (e.g., reward functions, policy optimization, or multi-agent RL environments), particularly applied to decision-making or simulation modeling
- Experience with agentic workflows, orchestration systems, Model Context Protocol (MCP), or Agent-to-Agent (A2A) communication patterns
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