• Lead technical discovery sessions to understand customer challenges, business objectives, and modernization initiatives. • Design solution architectures leveraging Mendix, ICX, AI services, and enterprise systems. • Conduct technical workshops, architecture sessions, and executive briefings. • Serve as a trusted advisor to customers throughout the sales cycle. • Deliver compelling business and technical demonstrations tailored to customer use cases. • Design and develop proof-of-concepts and prototype applications using Mendix. • Demonstrate integration with enterprise applications, APIs, databases, cloud platforms, and AI services. • Showcase best practices for application governance, scalability, security, and lifecycle management. • Position and demonstrate Intelligence Center X (ICX) as part of Siemens' broader AI and digital transformation strategy. • Help customers understand how to leverage enterprise data, AI, and intelligent automation to improve business outcomes. • Design and demonstrate AI-powered business applications utilizing Mendix, ICX, and Generative AI technologies. • Develop customer-specific demonstrations showcasing intelligent workflows, copilots, assistants, predictive insights, and automation scenarios. • Educate customers on AI architecture patterns including agentic AI, Retrieval-Augmented Generation (RAG), knowledge graphs, and enterprise AI governance.

• Manage, coach, counsel and develop department operations and assigned and staff • Review consumer complaints and responses; ensure responses are prompt and adhere to state/federal regulations • Ensure information requests from consumers are in compliance with CFPB requirements • Provide monthly consumer information request trends and reports to senior management • Maintain accurate investor reporting requirement records as specified in servicing agreements; ensure changes requested by investors are implemented • Establish procedures for the department and ensure proper controls are in place • Establish metrics/goals for research and mortgage resolution staff; manage achievement of goals • Support the Call Center on escalated issues and consumer improvement initiatives • Report to government agencies as required • Remain updated on loan servicing government regulations • Manage internal tracking systems and processes • Distribute work assignments to Special Loans staff through subordinate supervisors • Perform quality control reviews as needed • Prepare the department annual budget, expectations, and goals • Manage vendors used in departments under management • Develop products used in departments under management and assist in promoting those products • Request, create/prepare, update/revise, review, test, finalize/approve, and maintain the department’s policies and procedures; conduct training

• Support networking technologies such as Spectrum-X and work with customers on their technical challenges and requirements during pre-sales activities • Develop proof-of-concept materials for innovative technologies for use by early adopters • Gain customers’ trust and understand their needs to help design and deploy cutting-edge NVIDIA networking platforms to run AI and HPC workloads • Address sophisticated and highly-visible customer issues • Work closely with R&D teams to develop new features for customers • Help with product requirements along side engineering and product marketing

• Set up, adjust, and verify AI factory environments across multi-GPU and multi-node Linux clusters. • Ensure configurations align with guidelines for NCCL, collectives, and distributed training frameworks. • Own the execution of key AI/LLM benchmarks, including setup, orchestration, result collection, and analysis. • Investigate and resolve issues when training jobs or benchmarks fail, hang, or underperform. • Build and improve observability for AI factories (metrics, logs, traces, dashboards) to understand workload behavior and system health. • Develop automation (Python, Shell) for running benchmarks, collecting results, and performing regression checks • Examine communication patterns and NCCL usage for AI/LLM workloads, concentrating on collectives such as AllReduce and AllToAll. • Recommend changes to job configuration, parallelism strategies, and cluster settings to improve throughput, latency, and scaling efficiency. • Work closely with hardware, software, networking, datacenter, and product teams to prepare AI factories for customer use. • Contribute to documentation, guidelines, and readiness collateral that support internal collaborators and customer-facing teams.