Corporate Functions Senior AWS Cloud Engineer – VP III at 2001 SSB&T — Boston, MA

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

• 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.
• 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.
• 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.

• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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 mod