Wraithwatch
Wraithwatch was founded by alumni from SpaceX, Palantir, and Anduril to build the next generation of AI-powered cyber defense systems for the United States and its allies. We are deployed today to customers spanning aerospace, defense, manufacturing, and emerging technology.
Our core product, Wraithwatch Commander, is a continuously adaptive cyber defense platform utilizing generative artificial intelligence agents to autonomously model and construct a digital twin of an organizations entire IT and cybersecurity environment and analyze it for weaknesses, misconfigurations, and chains of possible attack. Specialized offensive and defensive AI agents work together in a process of adversarial co-evolution to detect novel attack paths that exist in a customer network and rapidly develop correlative defense strategies. Users can visualize, manipulate, and command the system through an intuitive and futuristic interface.
Responsibilities
As a Software Engineer, you will work with all components of Wraithwatchs architecture, including ensuring autonomous and smooth construction of advanced digital twin models of networks, coordinating communication and signaling between backend AI engines and workers, building data pipelines between Wraithwatch and third-party security products, and performing site reliability operations to ensure our customer deployments are resilient and maintain uptime. Note that we are a seed-stage startup with aggressive goals to disrupt the cybersecurity industry. You will routinely work long hours and weekends as needed. The upside is an opportunity to build a product at the leading edge of AI and cyber defense with real national security and private sector impact. Qualifications
Basic Bachelor's degree in computer science, engineering, or a STEM discipline 5+ years experience building and scaling distributed systems or complex backend infrastructure in Python or similar high-level language Proven ability to design reliable systems operating at scale, especially with high-throughput data processing Experience with container orchestration (Kubernetes), cloud-native infrastructure (AWS, Azure), and DevOps practices (CI/CD, monitoring, observability) Willingness to work extended hours and weekends as part of a fast-moving seed-stage startup Preferred Interest in modern machine learning or artificial intelligence capabilities, especially emerging subsets of Generative AI such as agentic behavior, tool calling, knowledge graph integration, retrieval augmented generation, etc., demonstrated through professional or side projects Experience building enterprise-grade cybersecurity products
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As a Software Engineer, you will work with all components of Wraithwatchs architecture, including ensuring autonomous and smooth construction of advanced digital twin models of networks, coordinating communication and signaling between backend AI engines and workers, building data pipelines between Wraithwatch and third-party security products, and performing site reliability operations to ensure our customer deployments are resilient and maintain uptime. Note that we are a seed-stage startup with aggressive goals to disrupt the cybersecurity industry. You will routinely work long hours and weekends as needed. The upside is an opportunity to build a product at the leading edge of AI and cyber defense with real national security and private sector impact. Qualifications
Basic Bachelor's degree in computer science, engineering, or a STEM discipline 5+ years experience building and scaling distributed systems or complex backend infrastructure in Python or similar high-level language Proven ability to design reliable systems operating at scale, especially with high-throughput data processing Experience with container orchestration (Kubernetes), cloud-native infrastructure (AWS, Azure), and DevOps practices (CI/CD, monitoring, observability) Willingness to work extended hours and weekends as part of a fast-moving seed-stage startup Preferred Interest in modern machine learning or artificial intelligence capabilities, especially emerging subsets of Generative AI such as agentic behavior, tool calling, knowledge graph integration, retrieval augmented generation, etc., demonstrated through professional or side projects Experience building enterprise-grade cybersecurity products
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