• Lead technical workshops to identify, refine, and prioritize high-impact AI and GenAI use cases aligned with business objectives. • Translate business problems into system design requirements and AI workflows. • Assess existing data platforms, pipelines, governance, and accessibility for AI workloads. • Evaluate data quality, lineage, security, and suitability for training, RAG, and inference patterns. • Design AI architectures that comply with enterprise security, privacy, and regulatory constraints (PII, PHI, internal policies). • Evaluate and design integrations across APIs, event streams, and existing systems. • Evaluate and recommend foundation models and AI services, including Amazon Bedrock, Amazon Nova, and open-source models. • Analyze tradeoffs across cost, latency, accuracy, and scalability. • Design GenAI patterns such as RAG, agent workflows, and inference pipelines. • Produce high-level and detailed AWS reference architectures for prioritized AI use cases. • Define phased implementation roadmaps that balance speed, risk, and long-term maintainability. • Identify PoC scope that can be executed within a short engagement. • Partner with stakeholders to develop ROI and TCO models for AI initiatives. • Provide cost modeling for model usage, data pipelines, infrastructure, and operations. • Deliver AI assessment findings and recommendations. • Create target-state AI platform architecture diagrams. • Summarize data readiness and compliance assessments. • Provide model evaluation and selection rationale. • Define phased implementation roadmap. • Design and validate PoC. • Prepare executive-ready presentations and documentation.