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 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 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.

What We Value

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.

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