Staff Performance Analysis Engineer

We are seeking an experienced Staff Engineer to lead the architecture, design, and large scale deployment of the ContextSensor, a core component of the ContextFabric platform. This role is central to achieving massive scale—100k+ installations across enterprise environments—and requires expertise in distributed systems, high-throughput data processing, and resilient service design. Because the ContextSensor incorporates AI models into its runtime, you will also play a key role in optimizing model execution on end user devices, ensuring performance, efficiency, and reliability. The ideal candidate thrives at the intersection of systems engineering, AI runtime optimization, and practical scalability challenges. You should be comfortable making critical tradeoffs, ensuring efficiency at the endpoint, and working cross-functionally with product, platform, and customer teams to ensure seamless deployment and adoption across diverse enterprise environments. Define the architecture and technical roadmap for the ContextSensor, balancing scalability, resilience, and ease of deployment. • Drive innovation in distributed system design, large-scale telemetry capture, and enterprise-scale deployment strategies. • Lead design reviews, ensure adherence to best practices, and provide deep technical mentorship across the engineering team. Scalable Implementation & Deployment • Build and optimize services capable of supporting 100k+ installations in enterprise-scale environments. • Lead development of deployment strategies for cloud-native and hybrid enterprise environments. • Develop self-service tooling, automation, and monitoring to reduce friction in large rollouts. • Ensure observability, monitoring, and diagnostic tools are embedded for reliable operation at scale. Optimize performance of client-side components running on end-user machines, with a focus on resource efficiency (CPU, memory, and power usage). • Data Processing & Performance Engineering • Architect and optimize pipelines for capturing, normalizing, and transmitting contextual data with low latency and high reliability. • Address large-scale data volume challenges, ensuring efficient ingestion and processing. • Collaborate with Security and Infrastructure teams to meet enterprise IT standards for installation and operation. Contribute to internal technical enablement by documenting best practices, deployment playbooks, and scaling strategies. 10+ years of experience in Desktop Application Development, with 6+ years focused on distributed systems, large-scale services, or data-intensive platforms. • Proven track record of designing and scaling a client application to tens of thousands of installations or more. • Expertise in service scalability, high-throughput data pipelines, and resilient architecture. • Strong programming and system design skills in C#, WPF, Python, Electron, HTML/CSS. • Experience with monitoring, observability, and performance optimization at scale. • Experience building AI or ML-adjacent infrastructure. • Prior success scaling SaaS or hybrid platforms into 100k+ deployment environments. • Experience in Mac OS APIs and programming with Objective C or Swift. Reliable deployment of the ContextSensor across 100k+ organizational endpoints. • Performance: Low-latency, high-throughput contextual data capture and AI model execution at scale. • Measured improvements in uptime, resilience, and fault tolerance in production environments. • Adoption: Smooth enterprise deployments with reduced time-to-value and minimal operational friction. •