Lead and develop engineers. Hire, coach, and grow a team spanning infrastructure, operations, and shared-platform software. Establish clear expectations, support career development, and foster an inclusive culture of technical excellence and accountability. Own the team's roadmap and delivery. Translate platform and product needs into priorities, architectural plans, and measurable outcomes. Balance feature delivery with reliability, security, technical debt, infrastructure cost, and operational sustainability. Guide shared-platform architecture. Lead the design and evolution of reusable services, libraries, interfaces, and runtime components used across real-time applications. Establish clear ownership boundaries and maintain compatibility as systems evolve. Advance low-latency software engineering. Guide improvements in concurrency, asynchronous execution, memory safety, data structures, and resource efficiency for high-throughput Linux services. Maintain a high bar for design reviews, code quality, and automated testing. Modernize distributed caching and state services. Lead client and server integration, migration, capacity planning, replication, failover, and observability for cache-backed serving capabilities. Ensure predictable behavior under timeouts, partial failures, and changing workloads. Enable model-backed serving and traffic management. Partner with machine learning and auction teams to integrate model scores and decisions into real-time services, including traffic shaping and dynamic pricing capabilities. Preserve latency budgets, decision correctness, fallback behavior, and experimentation controls. Evolve logging and streaming infrastructure. Improve high-volume data collection, buffering, batching, transport, and downstream integration. Address throughput, backpressure, data integrity, and recovery across distributed pipelines. Lead safe infrastructure modernization. Deliver infrastructure-as-code and shared-service migrations to Azure through staged validation, controlled cutovers, and practical rollback plans. Coordinate dependencies across networking, storage, and data-platform teams. Drive operational excellence. Improve service-level objectives, monitoring, alerting, diagnostics, and on-call practices. Guide incident response and blameless postmortems, turning recurring production issues into durable engineering improvements. Improve developer productivity and secure delivery. Advance build systems, CI/CD, deployment automation, configuration management, and reusable tooling. Embed security and privacy requirements into application and infrastructure design. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 3+ years of people management experience leading software engineering teams, including coaching, performance management, and career development. Experience designing, delivering, and operating large-scale distributed systems, including performance-sensitive backend services. Experience leading cross-team engineering initiatives involving shared platforms, infrastructure, or production-service modernization. Solid understanding of software architecture and production reliability, including concurrency, resource management, and distributed-system failure modes. Experience with high-performance C/C++ software on Linux, including multithreading, asynchronous I/O, memory ownership, profiling, and efficient data structures. Experience building shared libraries or foundational services adopted by multiple engineering teams, including interface evolution and backward compatibility. Experience with distributed caches or key-value systems such as Aerospike, Garnet, Redis, or comparable technologies, including replication, failover, capacity planning, and client integration. Experience with Kafka or comparable streaming systems and high-throughput logging or data-distribution pipelines. Experience integrating machine learning scores or model-backed decisions into latency-sensitive production services; model-training experience is not required. Experience with traffic shaping, rate limiting, admission control, or other mechanisms for balancing throughput, capacity, and business value. Experience operating Azure and hybrid infrastructure, including virtual machine scale sets, networking, storage, and infrastructure-as-code technologies such as Terraform or Bicep. Experience with configuration management tools such as Puppet or comparable systems, CI/CD pipelines, and automated build and test environments. Experience delivering migrations using feature flags, experimentation, shadow traffic, staged rollouts, and rollback strategies. Experience with observability technologies such as Grafana or OpenTelemetry and with service-level objectives, incident management, and operational automation. Experience with advertising auctions, pricing, inventory-quality controls, or other high-volume real-time transaction systems.