Corporate Functions Senior AWS Cloud Engineer – VP III

Corporate Functions Senior AWS Cloud Engineer – VP III Who We Are Looking For We are seeking a highly experienced, hands-on technology leader to serve as the Corporate Functions Senior AWS Cloud Engineer – VP III , responsible for designing, engineering, deploying, and supporting complex AWS-based applications and AI-enabled platforms across Corporate Functions Technology. This role is intended for a senior cloud engineer who can operate as a principal-level technical contributor with deep hands-on expertise across the AWS ecosystem. The successful candidate will be responsible for building secure, scalable, production-ready cloud solutions that support enterprise applications, intelligent assistants, AI-enabled workflows, automation, integrations, data services, and operationally resilient platforms. The ideal candidate has extensive experience deploying end-to-end applications into AWS, including networking, compute, application hosting, load balancing, security, data services, secrets management, observability, CI/CD, and production support. This individual must also have hands-on experience enabling AI capabilities within AWS, including Amazon Bedrock, AI service integrations, model endpoint connectivity, AI orchestration patterns, and secure deployment of AI-enabled applications. This is not a purely advisory or architecture-only role. The candidate must be able to actively engineer, configure, deploy, troubleshoot, automate, and support complex AWS environments while also guiding other engineers and development teams on cloud-native engineering best practices. Why This Role Matters Corporate Functions is expanding the use of cloud-native technologies, AI-powered business capabilities, intelligent automation, and modern application platforms across HR, Legal, Audit, Compliance, Risk, Realty, and other business domains. This role will help establish the engineering foundation required to: Deploy secure, scalable, and resilient applications into AWS. Enable AI-powered applications and intelligent business workflows. Support enterprise-grade architectures across application, data, integration, security, and observability layers. Implement reusable AWS engineering patterns that accelerate delivery. Improve cloud security, operational resilience, and production maturity. Support modernization of legacy platforms into cloud-native and AI-enabled solutions. Partner across application, architecture, cybersecurity, infrastructure, and business teams to deliver measurable business value. This is a highly visible senior engineering role that will directly influence how Corporate Functions builds, deploys, and operates modern AWS and AI-enabled solutions. What You Will Be Responsible For 1. AWS Cloud Engineering & Architecture Design, engineer, deploy, and support complex AWS solutions for enterprise business applications. Build secure, highly available, scalable, and resilient cloud environments. Implement AWS architectures across multiple availability zones. Establish reusable AWS reference architectures, deployment patterns, and engineering standards. Lead cloud modernization efforts for applications moving into AWS. Partner with architects and application teams to translate business and platform requirements into production-ready cloud solutions. Provide hands-on engineering leadership across design, build, release, troubleshooting, and support activities. 2. End-to-End AWS Application Deployment Deploy enterprise applications into AWS from infrastructure setup through production release. Engineer complete application environments across: VPC and network configuration Private and application subnets Load balancing Compute services Application hosting Data services Secrets and certificate management Monitoring and alerts Security controls CI/CD automation Support backend application deployment patterns including Tomcat, Java services, APIs, microservices, containers, and serverless workloads. Troubleshoot complex application, infrastructure, networking, and security issues. Ensure applications are production-ready, operationally supportable, and aligned with enterprise standards. 3. Required AWS Platform Expertise Serve as a subject matter expert across core AWS services, including: VPC Subnets Security Groups Route 53 Application Load Balancer Auto Scaling Groups EC2 ECS EKS Lambda API Gateway EventBridge Step Functions RDS Aurora PostgreSQL ElastiCache / Redis S3 Secrets Manager Certificate Manager CloudWatch CloudTrail IAM Systems Manager VPC Endpoints PrivateLink The candidate must be able to configure, deploy, troubleshoot, and support these services in complex enterprise environments. 4. AWS AI Engineering & Intelligent Application Enablement Design and deploy AWS-based AI-enabled applications and intelligent business platforms. Implement AI solutions using AWS-native services, including Amazon Bedrock and related AI/ML capabilities. Integrate applications with LLMs, model endpoints, AI services, enterprise APIs, and internal AI platforms. Engineer secure patterns for AI service invocation, prompt processing, response handling, audit logging, and operational monitoring. Support AI-enabled applications that interact with users, enterprise systems, workflow engines, databases, and external services. Implement responsible AI engineering controls including observability, traceability, guardrails, human oversight, logging, and escalation patterns. Partner with architecture, cybersecurity, data, risk, and business teams to ensure AI capabilities are secure, compliant, scalable, and operationally mature. 5. AWS-Native AI Orchestration & Agentic Patterns Build and support AWS-native orchestration patterns for AI-enabled workflows. Implement solutions leveraging: Amazon Bedrock Lambda Step Functions EventBridge API Gateway CloudWatch Secrets Manager IAM VPC Endpoints AWS-hosted application services Support enterprise AI deployment patterns involving tool calling, workflow orchestration, event-driven processing, and secure backend service execution. Engineer integration patterns that allow AI-enabled applications to interact with enterprise systems and business processes. Support Agent-to-Agent and system-to-system integration patterns where AI capabilities need to coordinate across internal and external platforms. Ensure AI workloads are observable, secure, auditable, resilient, and aligned with enterprise governance requirements. 6. Infrastructure Automation & DevOps Develop and maintain Infrastructure as Code for AWS environments. Automate environment provisioning, application deployment, configuration, and release management. Build and support CI/CD pipelines for cloud-native and AI-enabled applications. Partner with development teams to streamline deployment processes. Improve engineering productivity through reusable templates, automation scripts, and deployment patterns. Support DevOps, SRE, and operational excellence practices across cloud environments. 7. Security, Secrets Management & Cloud Governance Implement security controls across AWS application environments. Configure IAM roles, policies, access controls, encryption, secrets, certificates, and secure service-to-service communication. Support VPC endpoint and PrivateLink patterns for private connectivity. Ensure cloud environments meet enterprise standards for cybersecurity, data protection, auditability, resiliency, and compliance. Partner with Cybersecurity, Cloud Governance, Enterprise Architecture, Risk, and Infrastructure teams. Support architecture reviews, cloud governance approvals, risk assessments, and production readiness processes. 8. Monitoring, Observability & Production Support Implement monitoring, logging, tracing, alerting, and observability solutions for AWS-hosted applications. Utilize tools such as: CloudWatch CloudTrail Prometheus Grafana Application logs Infrastructure metrics Health checks Build dashboards and operational views for application and infrastructure supp