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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 support. • Perform root cause analysis and lead resolution of complex production issues. • Develop runbooks, operational procedures, monitoring standards, and support documentation. • Improve platform reliability, incident response, and operational maturity. 9. Enterprise Integration & Application Connectivity • Support secure integrations between AWS-hosted applications and enterprise platforms. • Build and support integration patterns involving: • Internal enterprise applications • Workday • ServiceNow • Microsoft 365 • SharePoint • Vendor SaaS platforms • Enterprise AI platforms • Data and reporting platforms • Implement API-based, scheduled, event-driven, and service-to-service integration patterns. • Ensure integrations are reliable, secure, observable, and production-ready. • Troubleshoot complex connectivity, authentication, data flow, and application interaction issues. 10. Technical Leadership & Engineering Excellence • Serve as a senior AWS engineering authority across Corporate Functions Technology. • Provide technical guidance to development teams, cloud engineers, data engineers, and delivery partners. • Lead technical design reviews, deployment reviews, code reviews, and operational readiness assessments. • Establish AWS engineering standards, reusable patterns, and best practices. • Mentor engineers on cloud-native development, AI deployment patterns, observability, security, automation, and production support. • Influence technical direction across multiple Corporate Functions initiatives. Must-Have Qualifications • 12+ years of experience in software engineering, cloud engineering, platform engineering, infrastructure engineering, or enterprise application delivery. • 8+ years of hands-on AWS engineering experience. • Proven experience deploying complex enterprise applications end-to-end into AWS. • Deep hands-on expertise with AWS networking, compute, security, data services, observability, and automation. • Strong experience designing and implementing secure multi-tier AWS architectures. • Required experience with AWS services including: • VPC • Subnets • Security Groups • Application Load Balancer • EC2 • ECS / EKS • Lambda • API Gateway • EventBridge • Step Functions • RDS / Aurora / PostgreSQL • ElastiCache / Redis • S3 • Secrets Manager • Certificate Manager • CloudWatch • CloudTrail • IAM • VPC Endpoints / PrivateLink • Required experience building or deploying AI-enabled applications within AWS. • Required experience with Amazon Bedrock or comparable cloud-based AI service integration. • Experience integrating applications with LLMs, model endpoints, enterprise AI platforms, or AI orchestration layers. • Strong understanding of AI deployment patterns, including prompt processing, service invocation, audit logging, observability, and responsible AI controls. • Experience with Infrastructure as Code, CI/CD pipelines, automated deployments, and DevOps practices. • Strong troubleshooting experience across cloud infrastructure, application services, networking, security, and production operations. • Ability to lead technical teams and influence engineering decisions without requiring direct management authority. • Strong communication skills with the ability to explain complex technical topics to application teams, architects, risk partners, and senior stakeholders. Preferred Qualifications • Experience with Databricks. • Experience building data pipelines, lakehouse solutions, or enterprise data processing frameworks. • Experience integrating AWS-hosted applications with enterprise data platforms. • Experience with Java, Python, SQL, or modern backen