• Serve as the primary AWS AI architecture partner for strategic clients, driving generative and agentic AI system design from discovery through production. • Lead architecture design using Amazon Bedrock (including foundation models and custom models), Bedrock AgentCore, AWS Strands Agents, and AWS AgentCore Gateway. • Design advanced RAG, Agentic RAG, and multi-agent orchestration architectures leveraging AWS-native services such as Lambda, Step Functions, API Gateway, DynamoDB, Aurora (pgvector), and OpenSearch. • Produce AWS reference architectures, architecture decision records (ADRs), and implementation roadmaps aligned to business objectives. • Validate feasibility through hands-on prototyping in Python using Bedrock SDKs, SageMaker, and serverless services. • Ensure architectures follow AWS security best practices (IAM, KMS, VPC, PrivateLink) and cost optimization principles. • Own architectural integrity from concept through production deployment on AWS. • Align solutions with AWS Well-Architected Framework pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. • Guide clients through tradeoff decisions across model selection (Bedrock FMs vs custom SageMaker models), latency, cost, governance, and compliance. • Accelerate time-to-value through reusable AWS accelerators, Infrastructure as Code (CloudFormation/Terraform/CDK), and CI/CD automation. • Continuously evaluate emerging AWS AI capabilities (Nova Forge, Nova 2 Sonic, Bedrock updates, and new AgentCore capabilities). • Provide architectural oversight to Forward Deployed Engineers and AWS delivery teams. • Establish best practices for MLOps on AWS including model lifecycle management, monitoring, and observability using SageMaker, CloudWatch, CloudTrail, and AWS Config. • Define governance, responsible AI guardrails, Bedrock Guardrails configuration, and security controls for enterprise environments. • Mentor engineers on AWS AI service integration, distributed systems design, and secure multi-account strategies. • Make principled tradeoffs under constraints related to privacy, compliance (SOC2, HIPAA, GDPR), cost, and operational complexity. • Partner with internal product, engineering, research, and customer success teams to evolve AWS-based AI offerings. • Contribute AWS reference architectures and reusable infrastructure modules to internal accelerators. • Support pre-sales engagements including architecture workshops, AWS migration strategy, and solution scoping. • Collaborate across distributed teams and client stakeholders across North America.