Job Summary
AI & Cloud Resiliency Architect Key Responsibilities Develop cloud and application architectures that are highly available, fault tolerant, and recoverable. Establish enterprise-wide resiliency principles, standards, architectural patterns, and governance guardrails. Identify and mitigate risks related to single points of failure, large blast-radius impacts, tight dependencies, scalability limitations, and system coupling. Design resilient Generative AI, AI agent, and multi-agent architectures. Define resiliency and architecture standards for Model Context Protocol (MCP) and AI tool integrations. Implement strategies for handling model and service failures, including fallback mechanisms, graceful degradation, retries, circuit breakers, and failure isolation. Architect serverless and event-driven solutions using AWS Lambda, SQS, SNS, DynamoDB, API Gateway. Define requirements for high availability, disaster recovery, RTO/RPO targets, observability, recovery processes, and resilience testing. Create reusable reference architectures, design patterns, resiliency checklists, and production-readiness frameworks. Collaborate with Application Development, Cloud Engineering, SRE, Security, and Operations teams to embed resiliency into solution design. Required Experience Proven expertise in application, system, and cloud architecture. Strong understanding of distributed systems, APIs, and event-driven/serverless architectures. Extensive AWS architecture experience Experience designing Generative AI and Agentic AI solutions. Knowledge of MCP, AI agents, RAG architectures, LLM integrations, and AI orchestration frameworks. Strong understanding of resiliency engineering, fault tolerance, scalability, observability, and disaster recovery. Experience developing enterprise architecture standards, reference models, and design guardrails. Experience working within banking, financial services, or other highly regulated industries. Hands-on experience with Amazon Bedrock or similar Generative AI platforms. Knowledge of AI governance, security, technology risk management, and operational resilience. Familiarity with SRE practices and chaos engineering methodologies.