• Lead technical discovery and solution positioning for enterprise AI infrastructure opportunities, translating business outcomes into reference architectures and value propositions. • Own pre-sales deliverables including architectures, diagrams, sizing, BOMs, proposals. • Deliver executive and technical presentations focused on NVIDIA AI Enterprise (NVAIE), LLM training/inference, and accelerated analytics. • Guide clients through technology selection, roadmap development, and business case creation for large-scale AI initiatives. • Architect end-to-end AI platforms using NVIDIA DGX/HGX, Blackwell (B100/B200), Hopper (H100/H200), Grace/Grace-Hopper (GH200), L40S, NVLink/NVSwitch, InfiniBand (NVIDIA Quantum), RoCE, and DPU offload patterns. • Design solutions leveraging AMD Instinct (MI300/MI300X) as appropriate, articulating trade-offs in CPU/GPU/DPU, interconnect topology, and cluster scale-out. • Integrate NVIDIA AI Enterprise components (CUDA, cuDNN, TensorRT, Triton Inference Server, RAPIDS) and common ML frameworks (PyTorch, TensorFlow) with orchestration platforms. • Experience integrating on-prem GPU clusters with cloud AI services (AWS SageMaker, Azure ML, GCP Vertex AI) for hybrid bursting and workload mobility. • Advise on MLOps platforms (MLflow, Kubeflow, Weights & Biases), CI/CD, and governance for multi-tenant AI environments. • Build and maintain relationships with NVIDIA, AMD, Run:AI, OEMs, and networking vendors, aligning campaigns with partner programs and incentives. • Contribute feedback to vendor engineering and product teams, coordinating joint enablement and reference designs. • Create repeatable assets such as validated designs, sizing calculators, POV guides, deployment runbooks, and competitive playbooks. • Mentor SEs and delivery consultants, leading internal training on AI scheduling, performance tuning, and operational best practices. • Lead proof-of-value (POV) and proof-of-concept (POC) engagements, including success criteria, benchmarking, and recommendations.

• Lead, develop, and retain a team of Sales/Solutions Engineers supporting enterprise sales cycles end-to-end. • Be the technical leader in strategic deals: run technical discovery, deliver executive-ready demos/whiteboards, and drive POV plans and success criteria. • Recruit, onboard, and ramp new SEs; establish consistent coaching, feedback, and performance expectations. • Build repeatable SE “win programs”: demo storylines, POV templates, mutual evaluation plans, competitive talk tracks, and security-review packages (questionnaires, architecture narratives, controls mapping). • Drive operational excellence with the Sales org: deal inspection, clean technical close plans, and strong opportunity hygiene in Salesforce. • Serve as the voice of the field to Product/Engineering: synthesize patterns from prospects/customers, influence roadmap, and ensure tight closure of feedback loops. • Stay current on identity security and adjacent trends to help position our “modern IGA” approach effectively in customer conversations. • Travel to customers and internal touchpoints as needed (typically ~25–50%).

• Advising our clients and independently designing, realizing, and implementing tailored solutions based on the TIVITY platform • Creating end-to-end solutions — from the initial idea, through detailed user stories and mockups, to the finished product • Acting as the central interface between clients and the project/development team to ensure project success • Conducting in-depth product and competitive analyses of innovative and market-leading software solutions • Facilitating workshops to identify solutions for complex, technically demanding subject areas

• Work closely with cross-functional teams, especially AI/Data Science experts, to gather requirements from AI projects. • Ensure the cloud platform is designed and delivered to meet project needs. • Take ownership with a high sense of responsibility to develop independent solution proposals. • Provide clear recommendations and drive topics proactively. • Ensure operational transition from project implementation to stable operational running of the platform. • Maintain comprehensive documentation and facilitate knowledge transfer. • Design, develop, and implement AI solutions using machine learning and deep learning. • Manage and automate cloud infrastructure in Azure and GCP, leveraging Infrastructure as Code tools. • Build, maintain, and monitor CI/CD pipelines using GitHub Actions or Azure DevOps. • Oversee secure integration of AI providers and manage identity and access via Microsoft Entra ID.