State Street
State Street
State Street ir globāls finanšu pakalpojumu uzņēmums, kas apkalpo institucionālos investorus, piedāvājot ieguldījumu pārvaldības un ieguldījumu apkalpošanas risinājumus. Tā pakalpojumi ietver aktīvu pārvaldīšanu, glabāšanas pakalpojumus un ieguldījumu izpēti, ko nodrošina ekspertīze finanšu, finanšu tehnoloģiju un banku darbības jomā. Uzņēmums palīdz klientiem pārvaldīt sarežģītas ieguldījumu darbības, izmantojot datus, atziņas un darbības iespējas, lai uzlabotu efektivitāti un atbalstītu finanšu lēmumu pieņemšanu.

Senior AWS Cloud Engineer (VP III) - Boston Onsite

Lead secure, resilient AWS and AI platform engineering for State Street’s institutional finance business. Own cloud deployment, automation, observability, modernization, and production support across Corporate Functions.

Apraksts

  • Design, engineer, deploy, and support complex AWS solutions for enterprise applications
  • Build secure, highly available, scalable, and resilient multi-availability-zone cloud environments
  • Define reusable AWS reference architectures, deployment patterns, and engineering standards
  • Lead modernization initiatives for applications migrating to AWS
  • Convert business and platform requirements into production-ready cloud designs
  • Deploy enterprise applications from initial infrastructure configuration through production release
  • Configure VPCs, subnets, load balancing, compute, hosting, data services, secrets, certificates, monitoring, security controls, and CI/CD automation
  • Support Tomcat, Java services, APIs, microservices, containers, and serverless workloads
  • Diagnose application, infrastructure, networking, and security problems
  • Design and deploy AWS-based AI applications and intelligent business platforms
  • Connect applications with LLMs, model endpoints, AI services, enterprise APIs, and internal AI platforms
  • Implement secure AI invocation, prompt and response handling, audit logging, monitoring, guardrails, human oversight, and escalation workflows
  • Create AWS-native AI orchestration and agentic workflows with Bedrock, Lambda, Step Functions, EventBridge, API Gateway, CloudWatch, Secrets Manager, IAM, and VPC Endpoints
  • Develop and maintain Infrastructure as Code and CI/CD pipelines
  • Automate environment provisioning, application deployment, configuration, and release processes
  • Apply AWS security controls, IAM, encryption, secrets management, certificates, private connectivity, governance, and compliance practices
  • Deliver monitoring, logging, tracing, alerting, dashboards, and observability capabilities
  • Conduct root cause analysis and resolve complex production incidents
  • Create runbooks, operating procedures, monitoring standards, and support documentation
  • Maintain secure integrations with Workday, ServiceNow, Microsoft 365, SharePoint, vendor SaaS, enterprise AI, data, and reporting platforms
  • Lead technical design, deployment, code, and operational readiness reviews
  • Advise and mentor engineers in cloud-native development, AI delivery, observability, security, automation, and production support

Prasības

  • At least 12 years of experience in software, cloud, platform, infrastructure engineering, or enterprise application delivery
  • At least 8 years of hands-on AWS engineering experience
  • Demonstrated success deploying complex enterprise applications end to end on AWS
  • Advanced practical knowledge of AWS networking, compute, security, data services, observability, and automation
  • Strong background designing and implementing secure, multi-tier AWS architectures
  • Experience with 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, and VPC Endpoints/PrivateLink
  • Experience building or deploying AI-enabled applications on AWS
  • Experience integrating Amazon Bedrock or a comparable cloud AI service
  • Experience connecting applications to LLMs, model endpoints, enterprise AI platforms, or AI orchestration layers
  • Knowledge of AI delivery patterns, prompt processing, service invocation, audit logging, observability, and responsible AI controls
  • Experience with Infrastructure as Code, CI/CD, automated deployments, and DevOps methods
  • Strong troubleshooting ability across cloud infrastructure, application services, networking, security, and production operations
  • Ability to lead technical teams and shape engineering decisions without direct reporting authority
  • Clear communication skills for discussing complex technical subjects with application teams, architects, risk partners, and senior stakeholders
  • Preferred experience with Databricks, data pipelines, lakehouse systems, enterprise data platforms, Java, Python, SQL, backend frameworks, containers, Kubernetes, Agent-to-Agent integration, enterprise AI orchestration, workflow-based AI, Corporate Functions, or regulated industries
  • AWS Professional-level certification is strongly preferred
  • AWS AI/ML, Security, DevOps, or Architecture certification is preferred
  • Databricks certification is advantageous

Priekšrocības

  • 401(k) retirement savings plan with company match
  • Basic life insurance
  • Medical insurance
  • Dental insurance
  • Vision insurance
  • Long-term disability coverage
  • Optional supplemental insurance coverage
  • Paid vacation
  • Paid sick leave
  • Short-term disability coverage
  • Family care and responsibility support
  • Employee Assistance Program
  • Annual performance-based incentive compensation
  • Selected tax-advantaged savings plans
  • Inclusive professional development opportunities
  • Flexible work-life support
  • Paid volunteer days
  • Employee networks

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