• Implement production AI / ML workloads using Ray and Anyscale, such as: - Distributed model training - Scalable inference and serving - Data preprocessing and feature pipelines • Advise customers on ML system architecture, including: - Application design for distributed execution - Resource management and scaling strategies - Reliability, fault tolerance, and performance tuning • Guide customers through architectural and operational changes required to adopt Ray and Anyscale effectively • Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows • Support CI/CD, monitoring, retraining, and operational best practices • Help customers transition from experimentation to production-grade ML systems • Enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance • Contribute feedback from the field to product, engineering, and education teams • Help develop reference architectures, examples, and best practices based on real customer use cases

• Provides support to clients in the usage, and maintenance of their software programs as necessary. • Obtains and maintains business software certification for products as required. • Responds to client requests for software and accounting related assistance. • Performs data conversions. • Implements processes including project planning, system installation, and system setup of the accounting systems. • Assist other team members with miscellaneous assignments as required.

• Define the Technical Vision: Lead the creation of comprehensive architectural strategies and blueprints that align with long-term business goals. • Architectural Governance: Drive governance by setting standards, conducting deep-dive reviews, and managing technical risk across projects. • Platform Evolution: Design and evolve cloud-native systems with a relentless focus on scalability, security, and observability. • The "Technical Quarterback": Partner with Digital Product Managers and Product Integration Leads in a "Three-in-a-Box" model. • Contract-First Design: Define or facilitate integration specifications, API contracts (OpenAPI/Swagger), and event schemas (Kafka). • Hands-on Guidance: Work closely with engineering teams to troubleshoot technical roadblocks. • Lead Modernization: Drive initiatives to migrate from monolithic legacy systems to service-oriented architectures. • AI-Native Leverage: Pioneer the use of AI to revolutionize architecture. • Cultivate Excellence: Mentor senior engineers and architects, cultivating a culture of system thinking and technical excellence. • Build a "T-Shaped" Team: Recruit and lead a team of architects who combine broad system views with deep technical specializations.

• Collaborate with prospects to determine if their applications fit Temporal’s platform well. • Educate customers and prospects on the technical benefits and limitations of Temporal’s platform and cloud service. • Position Temporal as a leading solution against competing technologies and architectural patterns. • Foster an environment within customer engineering organizations to increase the adoption and expansion of Temporal in production environments. • Partner closely with Account Executives to develop and execute comprehensive account plans. • Manage and nurture relationships with technical decision-makers within customer organizations, ensuring they fully leverage Temporal’s capabilities.