• Build, implement, and optimize GPU communication kernels that underpin collective and point-to-point operations in large-scale AI systems. • Leverage deep knowledge of GPU architecture—thread scheduling, memory hierarchy, execution pipelines—to improve kernel efficiency, minimize latency, and overlap computation with communication. • Develop GPU-resident communication primitives and device-side APIs that enable fine-grained, kernel-initiated data movement across nodes and accelerators. • Profile and tune GPU kernels end-to-end, identifying bottlenecks at the intersection of compute, memory, and network, and driving targeted optimizations. • Collaborate with network software, hardware, and AI framework teams to co-design communication strategies that align with GPU execution patterns and emerging model architectures. • Build proofs-of-concept, conduct experiments, and perform quantitative modeling to evaluate and validate new communication strategies before committing them to production. • Contribute to the evolution of programming models that expose GPU-aware networking capabilities to application developers.

• Design and Architecture: Structure the logical layer by defining domain boundaries and designing the integration of the mainframe environment with new architectures such as microservices, OpenShift, and cloud environments. • Replatforming and Code Modernization: Provide technical leadership for the transition and modernization of legacy code, applying practical knowledge of portability, performance, and compilers (preparing systems for COBOL migration strategies to other languages). • Integrations and APIs: Develop and architect complex, secure interfaces to enable communication between logic extracted from the mainframe and open platforms (such as Linux/Unix environments). • Technical Leadership and Mentorship: Serve as the technical bridge between legacy and the new ecosystem, upskilling the current team in new technologies, mitigating production risks (parallelism and batch processing), and defining safe strategies for integrated testing.

• Develop technical solutions using the Pega platform (version 8+). • Build reusable, scalable components within the application's architecture. • Ensure best practices for development and code maintenance. • Translate functional requirements into well-structured technical solutions. • Collaborate with business analysts and developers to define solutions. • Develop and execute unit tests. • Participate in integration testing to validate applications. • Support the team in troubleshooting technical issues. • Propose continuous improvements to existing solutions. • Produce and maintain technical documentation for solutions. • Contribute to the team's repository of best practices.

• Assess legacy application portfolios, identify modernization opportunities, and develop technical roadmaps aligned with business outcomes. • Collaborate with stakeholders to understand business requirements and translate them into scalable, secure, and cost-effective software solutions. • Conduct technical discovery and strategy workshops to identify pain points, define modernization approaches, and guide solution design on topics such as microservices, cloud-native architecture, DevOps, and CI/CD. • Serve as a trusted technical advisor and subject matter expert on cloud technologies and software architecture, ensuring solutions align with client objectives. • Work with internal stakeholders to define scope, develop cost estimates and labor projections, and prepare Statements of Work (SOWs), product pricing, and RFP/RFI responses. • Design reference architectures, solution patterns, and migration frameworks that balance cost, maintainability, security, and performance. • Architect full-stack solutions that deliver measurable business value and enable teams to learn, iterate, and adopt modern delivery practices effectively. • Provide hands-on development leadership, coding alongside teams when needed. • Act as a thought leader by speaking at industry events, publishing white papers, and contributing to case studies.