Corporate Functions Senior AWS Cloud Engineer - VP III

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.

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.

- 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.

- 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.

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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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 backend development frameworks. - Experience with containerized workloads and Kubernetes-based deployments. - Experience with Agent-to-Agent integration patterns, enterprise AI orchestration, or workflow-driven AI solutions. - Experience supporting Corporate Functions domains such as HR, Legal, Audit, Compliance, Risk, Security, Realty, or Finance. - Experience within financial services or another highly regulated industry. - AWS Professional-level certifications strongly preferred. - AWS AI/ML, Security, DevOps, or Architecture certifications preferred. - Databricks certification is a plus.

- Deep hands-on AWS engineering capability. - Ability to build and operate complex solutions, not just design them. - Strong understanding of AI-enabled application patterns. - Practical cloud security and production support mindset. - Strong ownership and accountability. - Ability to simplify complex technical challenges. - Engineering excellence and attention to detail. - Continuous learning and innovation. - Strong partnership across business, application, architecture, cybersecurity, infrastructure, and data teams. - Ability to mentor others and raise the overall technical maturity of the organization.