AI & Cloud Resiliency Architect
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
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Original job description
Position- AI & Cloud Resiliency Architect
Location - Scarborough, ON
Job Description.
We are looking for an AI & Cloud Resiliency Architect to lead the design of scalable, highly available, and resilient cloud and AI solutions.
The role is focused on application and system architecture, defining resiliency standards, reference architectures, and engineering best practices across AWS, Generative AI, Agentic AI, and event-driven/serverless environments.
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.
More about this job
Responsibilities
Design scalable, highly available, and resilient cloud, application, and AI architectures, and establish enterprise resiliency standards, patterns, and governance guardrails. Define recovery and observability requirements, create reusable architecture and production-readiness resources, and collaborate with engineering, security, SRE, and operations teams to embed resiliency into solutions.
Requirements
Requires extensive experience in application, system, and AWS cloud architecture, distributed systems, serverless and event-driven solutions, and resiliency engineering. Also requires experience with Generative AI and Agentic AI - including MCP, RAG, LLM integrations, and AI orchestration - as well as enterprise architecture standards and work in regulated industries.
Skills
- Cloud Architecture
- Application Architecture
- AWS
- Generative AI
- Agentic AI
- Distributed Systems
- Event-Driven Architecture
- Serverless Architecture
- Resiliency Engineering
- Disaster Recovery
- Fault Tolerance
- Model Context Protocol
- Amazon Bedrock
- Site Reliability Engineering
- Chaos Engineering
- AI Governance
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Security & Safety
- Consulting
Keywords
- AWS
- Amazon Bedrock
- Generative AI
- Agentic AI
- AI Agents
- Multi-Agent Architectures
- Model Context Protocol
- RAG
- LLM Integrations
- AI Orchestration
- Distributed Systems
- APIs
- AWS Lambda
- Amazon SQS
- Amazon SNS
- Amazon DynamoDB
- Amazon API Gateway
- Event-Driven Architecture
- Serverless Architecture
- Resiliency Engineering
- Fault Tolerance
- High Availability
- Disaster Recovery
- RTO/RPO
- Observability
- Circuit Breakers
- Graceful Degradation
- AI Governance
- Site Reliability Engineering
- Chaos Engineering