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MixMode is a leading provider of AI-powered cybersecurity solutions at scale, pioneering a patented third-wave, context-aware AI approach that automatically learns and adapts to dynamic environments. The MixMode platform delivers self-supervised, real-time threat detection for known and unknown threats across cloud, hybrid, and on-premises environments. Large organizations with big data workloads – including those in enterprise, critical infrastructure, US Department of War and US Intelligence Community – trust MixMode to defend their most important assets. Backed by PSG and Entrada Ventures, MixMode is headquartered in Santa Barbara, California. Learn more at  www.mixmode.ai . Job Summary:  We are hiring a Senior Software Engineer, based in the United States, to enhance the reliability, performance, and scalability of our production AI systems. We value clear thinking, incremental improvement, and engineers with real production incident experience. This role focuses on understanding, refining, and strengthening existing distributed services across application, database, and container orchestration layers. You will collaborate with ML researchers to make our systems more robust, maintainable, flexible, and scalable. This is a remote position but requires the ability to travel to the MixMode headquarters in Santa Barbara for in person meetings a few times a year. What you’ll be doing (responsibilities): Own the reliability, performance, and operational health of production AI services Refactor and harden existing systems to improve resilience, clarity, and maintainability Diagnose and resolve issues across distributed services, data pipelines, and storage layers Design and implement monitoring, alerting, and debugging tools for high-availability systems Partner with researchers and engineers to productionize predictive systems at scale Establish best practices for testing, deployment, capacity planning, and incident response Contribute to incident response and postmortems, driving continuous improvement What you’ll need to bring (qualifications): Ability to travel to our office in Santa Barbara, CA, a few times per year 7+ years of professional software engineering experience Strong proficiency in Python and at least one JVM language (Java, Scala, Kotlin) Proven experience designing, building, and operating distributed systems in production Strong understanding of service architecture, concurrency, resource management, and distributed failure modes Experience operating Kubernetes deployments  Strong experience with relational databases, including query performance analysis, indexing, and connection management Demonstrated ability to diagnose and resolve performance, scalability, and reliability issues across system layers Experience implementing automated testing and production observability (logging, metrics, tracing) Experience collaborating with ML or data science teams (deep ML expertise is not required) Ability to improve system architecture and engineering practices through design, code review, and mentorship Our Interview Process: Our interview process focuses on real-world production experience and practical systems thinking. We assess how you reason about distributed systems, refactor existing code, and operate under real constraints—not abstract puzzles. We support the use of AI tools in our development, but we want to understand your capabilities first. No AI tools will be allowed for remote interviews early in the process. The process includes: Conversations about systems you’ve personally owned, improved, and operated in production A live refactoring and testing exercise in your choice of Java, Kotlin, or Scala, centered on improving existing code without changing behavior A distributed systems discussion covering performance, state management, failure modes, and debugging under load An ML production discus