• Build and lead a high-performing Core Platform Engineering team that: • Rapidly improves scalability, reliability, and observability of the core backend platform • Establishes systematic load testing, regression detection, and performance benchmarking practices • Drives measurable reductions in latency, error rates, and infrastructure cost per transaction • Leverages modern tooling, including AI-assisted analysis, to accelerate bottleneck identification and remediation • Partners closely with application engineering and Cloud Operations to ensure platform stability under real-world production load • Own and drive the performance, scalability, and reliability roadmap for the backend platform in close partnership with the CTO and engineering leaders • Prioritize performance and stability investments while balancing near-term delivery commitments. • Establish practical performance engineering practices, including load testing, benchmarking, and regression detection. • Proactively identify and eliminate performance bottlenecks to ensure fast, responsive user experiences at scale. • Design and execute realistic production-scale load testing scenarios that mirror customer behavior. • Establish performance regression gates in CI/CD pipelines. • Drive systematic root-cause analysis of production performance incidents. • Quantify and publish performance baselines and improvement targets. • Establish performance baselines and drive measurable improvements in throughput, latency, and resource efficiency. • Drive excellence in relational database architecture across MySQL and PostgreSQL environments in AWS (RDS/Aurora). • Lead database optimization strategies, indexing improvements, and schema evolution practices. • Partner with Cloud Operations to align infrastructure and data-layer scaling strategies. • Improve transactional integrity, concurrency handling, and data reliability at scale. • Lead query optimization initiatives based on real production workload analysis. • Identify and resolve lock contention, connection pool saturation, and concurrency bottlenecks. • Partner with Cloud Operations to right-size database infrastructure based on performance data. • Strengthen metrics instrumentation, structured logging and tracing across backend services. • Partner with SRE and Cloud Operations to enhance diagnostic capabilities and operational transparency. • Define measurable performance and reliability KPIs. • Ensure comprehensive instrumentation across critical backend paths. • Correlate load testing results with runtime metrics and tracing data. • Improve mean time to detect (MTTD) and mean time to resolve (MTTR) for performance incidents. • Engage directly in cross-team architectural design reviews, complex system decisions, and strategic refactoring initiatives. • Provide technical mentorship and elevate backend engineering standards. • Balance strategic direction-setting with practical, hands-on execution where needed. • Serve as a senior escalation point for complex backend performance or architectural challenges. • Clarify backend platform ownership boundaries in partnership with Product Engineering and Cloud Operations. • Recruit and develop a team of strong backend, database, and platform engineers. • Set clear expectations for engineering rigor, delivery accountability, and code quality. • Foster a culture of accountability, speed, craftsmanship, and continuous improvement. • Partner effectively with Product Engineering and Cloud Operations to ensure cohesive platform evolution. • Build a strong team capable of independently owning critical platform domains. • Influence engineering standards and platform practices across multiple application teams through collaboration and technical leadership.

• Build and lead a high-performing Core Platform Engineering team that: • Rapidly improves scalability, reliability, and observability of the core backend platform • Establishes systematic load testing, regression detection, and performance benchmarking practices • Drives measurable reductions in latency, error rates, and infrastructure cost per transaction • Leverages modern tooling, including AI-assisted analysis, to accelerate bottleneck identification and remediation • Partners closely with application engineering and Cloud Operations to ensure platform stability under real-world production load • Own and drive the performance, scalability, and reliability roadmap for the backend platform in close partnership with the CTO and engineering leaders, ensuring the platform scales with aggressive product and customer growth. • Prioritize performance and stability investments while balancing near-term delivery commitments. • Establish practical performance engineering practices, including load testing, benchmarking, and regression detection. • Proactively identify and eliminate performance bottlenecks to ensure fast, responsive user experiences at scale. • Design and execute realistic production-scale load testing scenarios that mirror customer behavior. • Establish performance regression gates in CI/CD pipelines. • Drive systematic root-cause analysis of production performance incidents. • Quantify and publish performance baselines and improvement targets. • Establish performance baselines and drive measurable improvements in throughput, latency, and resource efficiency. • Drive excellence in relational database architecture across MySQL and PostgreSQL environments in AWS (RDS/Aurora). • Lead database optimization strategies, indexing improvements, and schema evolution practices. • Partner with Cloud Operations to align infrastructure and data-layer scaling strategies. • Improve transactional integrity, concurrency handling, and data reliability at scale. • Lead query optimization initiatives based on real production workload analysis. • Identify and resolve lock contention, connection pool saturation, and concurrency bottlenecks. • Strengthen metrics instrumentation, structured logging and tracing across backend services. • Partner with SRE and Cloud Operations to enhance diagnostic capabilities and operational transparency. • Define measurable performance and reliability KPIs. • Engage directly in cross-team architectural design reviews, complex system decisions, and strategic refactoring initiatives. • Provide technical mentorship and elevate backend engineering standards. • Recruit and develop a team of strong backend, database, and platform engineers.

• Identify, track, manage, and report on assigned tasks and work items across multiple projects • Coordinate cross‑functional efforts related to features, game content, events, testing, localization, publishing initiatives, product extensions, and user engagement • Review development schedules and roadmaps, providing informed feedback and recommendations • Collaborate closely with internal and external partners to resolve blockers and maintain progress toward development and release milestones • Communicate clear, regular status updates on critical work items to stakeholders at multiple levels • Actively improve and unblock workflows by leveraging existing tools or implementing new processes as needed • Produce clear, readable reports and dashboards for a wide range of audiences, from individual contributors to leadership • Organize and lead meetings effectively, ensuring action items are documented, tracked, and followed through • Provide flexible support to other producers and project managers as project needs evolve

• Deliver our Product Roadmap: Translate product vision into a technical strategy with clear sequencing (now/next/later). Execute the roadmap through a highly accountable team, balancing immediate product velocity with the management of technical debt to ensure our ability to scale long-term. • Cultivate Talent, Partnerships, and Communication: Lead a high-performance team of Engineers in deep partnership with Product Management, Data Science, and Data Operations. • Facilitate an Engineering and Data Science partnership that turns R&D, such as ML models, into production features. Do this with speed to minimize the lag between innovation and deployment. • Support internal analytics users such that they can configure, query, and QA our data efficiently, so we can release best-in-class analytics products. • Communicate complex technical topics clearly to both subject matter experts and non-technical generalists to align stakeholders and manage incentives across the organization. • Architect our data platform for both today and the future: Guarantee our data infrastructure is reliable, performant, and solves specific business questions. • Ensure we are managing the tradeoffs between short-term and long-term technical strategy decisions. • Focus both on the data infrastructure that allows us to deliver customer value as well as the specific insights & analytics we provide on top of that infrastructure. • Lead AI Initiatives: Direct Antenna’s AI strategy. Implement AI technologies to enhance internal productivity, scale data collection & cleansing, and improve customer interfaces.