S

State Street

Holds assets for institutions and runs index funds

Senior AWS Cloud Engineer VP 3

Full-TimeUpdated on 10/23/2026Deadline 10/31/26
$110k - $207.5k/yr+ Annual performance-based awards
Expert
Boston, MA, USA+1 moreMore locations: Princeton, NJ, USA
In Person
DevOps & InfrastructureCloud Engineering
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • At least 12 years of experience in software engineering, cloud engineering, platform engineering, infrastructure engineering, or enterprise application delivery.
  • At least 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.
  • Experience with VPC, subnets, security groups, Application Load Balancer, EC2, ECS or EKS, Lambda, API Gateway, EventBridge, Step Functions, RDS, Aurora, PostgreSQL, ElastiCache or Redis, S3, Secrets Manager, Certificate Manager, CloudWatch, CloudTrail, IAM, VPC Endpoints, and PrivateLink.
  • Experience building or deploying AI-enabled applications within AWS.
  • Experience with Amazon Bedrock or comparable cloud-based AI service integration.
  • Experience integrating applications with large language models, model endpoints, enterprise AI platforms, or AI orchestration layers.
  • 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.
  • 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.
  • Ability to explain complex technical topics to application teams, architects, risk partners, and senior stakeholders.
Responsibilities
  • 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 application environments spanning 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, and 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.
  • Configure, deploy, troubleshoot, and support core AWS services in complex enterprise environments.
  • Design and deploy AWS-based AI-enabled applications and intelligent business platforms.
  • Integrate applications with large language models, 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.
  • Support enterprise AI deployment patterns involving tool calling, workflow orchestration, event-driven processing, and secure backend service execution.
  • Engineer integrations that allow AI-enabled applications to interact with enterprise systems and business processes.
  • Support Agent-to-Agent and system-to-system integration patterns 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 using tools such as CloudWatch, CloudTrail, Prometheus, Grafana, application logs, infrastructure metrics, and 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, including Workday, ServiceNow, Microsoft 365, SharePoint, vendor SaaS platforms, enterprise AI platforms, and 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.
Desired 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.
  • AWS AI/ML, Security, DevOps, or Architecture certifications.
  • Databricks certification.

About the company

S

State Street

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Website

State Street holds and services investments for pension funds, insurers, fund companies, and other large institutions, and it also runs index funds through State Street Investment Management. It launched the first US-listed exchange-traded fund, the SPDR S&P 500 ETF Trust, in 1993, and in 1924 it became custodian of the first US mutual fund. As a custody bank, it safekeeps clients' stocks and bonds, completes their trades, calculates what their funds are worth, and lends their securities to other investors. It earns fees on the assets it services and manages, plus income from currency trading and from interest on client cash. State Street traces its roots to a bank chartered in 1792 and is based in Boston, Massachusetts.

Company Size

10,001+

Company Stage

IPO

Headquarters

Boston, Massachusetts

Founded

1792

Get referred to State Street

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Simplify Jobs

Simplify's Take

What believers are saying

  • Fees, not lending, drive results: fees were 79% of revenue and grew 17% in the June 2026 quarter.
  • Equity has gained value: shares rose 36% from January to October 2026, beating custody rival Northern Trust's 23%.
  • Tech roles lead hiring: 477 of State Street's 1,133 open jobs in October 2026 were in information technology.

What critics are saying

  • Cuts continue despite record revenue: State Street booked $190 million in layoff charges from October 2025 to March 2026.
  • Its closest rival is more profitable: BNY kept 40% of mid-2026 revenue as pre-tax profit, versus State Street's 34%.
  • Legal risk lingers: Vanguard paid $29.5 million in March 2026 to exit an 11-state coal antitrust suit State Street fights.

What makes State Street unique

  • It doubles as a fund giant: it managed $6.3 trillion in June 2026, nearly triple custody rival BNY's $2.2 trillion.
  • Rival fund firms run on its back office: it services over 3,000 ETFs, about 39% of global ETF assets.
  • Fund managers trade through its software: it bought trading-system maker Charles River for $2.6 billion in 2018.

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Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Life Insurance
  • Disability Insurance
  • Flexible Work Hours
  • Remote Work Options
  • Professional Development Budget
  • Tuition Reimbursement
  • Paid Holidays
  • Employee Referral Bonus

Growth & Insights and Company News

6 month growth

-8%

1 year growth

-8%

2 year growth

-8%
Yahoo Finance
Oct 18th, 2026
State Street Q3 profit per share jumps 33% to $3.69 as revenue hits $4B

State Street reported a 33% year-over-year rise in third-quarter per-share earnings to $3.69. Total revenue grew 13% to $4 billion, the company said on its October 14, 2026 earnings call. Net interest income rose 21% to $864 million, driven by a wider net interest margin and higher average interest-earning assets. State Street expects over 500 basis points of positive operating leverage in 2026. The bank won a servicing mandate from one of the largest US registered investment advisors, pairing its front-office software with custody services. Alternative asset servicing fees grew at a double-digit rate. Assets under custody and administration reached a record $59.2 trillion.

SaasRise
Oct 17th, 2026
AI cloud-spending split deepens divide between funded SaaS leaders and cash-strapped players.

AI cloud-spending split deepens divide between funded SaaS leaders and cash-strapped players. SaasRise - Oct 17, 2026 New data shows a widening gap as large SaaS providers pour record dollars into AI-driven features, while indie hackers and mid-market firms scramble with limited cash and risky infrastructure choices. The split threatens expansion revenue for the stretched and accelerates moats for the funded. Why it matters. The AI cloud-spending divide creates a two-tier SaaS market. Funded players can accelerate AI-driven product development, lock in expansion revenue, and build defensible moats that attract premium valuations. Meanwhile, cash-strapped firms risk stagnation, higher churn, and reduced competitive relevance. For operators, the split forces a strategic choice: double-down on AI spend and secure financing, or double-down on lean, product-led growth and avoid costly infrastructure missteps. Investors must recalibrate risk models, weighting AI spend efficiency and cash runway more heavily than ever. Long-term, the split could catalyze consolidation. Larger SaaS platforms may acquire niche AI-focused startups to fill feature gaps, while smaller firms might spin out AI-lite modules to remain viable. The pressure on mid-market SaaS to either secure deep funding or adopt ultra-efficient cloud stacks will shape the next wave of category creation and competitive moats in the industry. Key points. * State Street's SaaS platform revenue rose 5% YoY to $175 M; software ARR grew 8% to $442 M. * Indie hackers: only 8-10% clear $10K MRR; median lifetime earnings near zero. * Phillip Merrick (pgEdge) warned that mis-chosen databases can force costly re-engineering for AI workloads. * John Turner Jr. (Regions Financial) noted slowing activity due to rising costs and economics challenges. * AI-focused sessions at TechCrunch Disrupt 2026 signal strong enterprise demand for AI-native infrastructure. Analysis. The emerging AI spend bifurcation mirrors past technology cycles where early adopters reap outsized returns while laggards fall behind. In the early 2010s, cloud-first firms that secured large credit lines could lock in discounted compute, creating cost advantages that persisted for years. Today, AI-native infrastructure is the new commodity, and the capital intensity is even higher. Companies like State Street, with $4 B in total revenue, can absorb the premium on GPU instances and still post double-digit ARR growth. Their ability to bundle AI features into existing SaaS contracts translates into higher net-retention and cross-sell opportunities, reinforcing a virtuous cycle of growth and valuation uplift. For the stretched cohort, the challenge is twofold. First, the cost curve for AI services is steep; without deep pockets, a modest increase in cloud spend can erode margins dramatically. Second, the technical debt of choosing the wrong database or monitoring stack compounds the problem, as Merrick and Ramachandran both highlight. The result is a higher likelihood of performance incidents, customer churn, and ultimately, a weaker competitive moat. Some mid-market firms may attempt to mitigate this by leveraging outsourced finance platforms - K-38 Consulting's guide shows a growing market for fractional CFOs that can help align spend with revenue forecasts. However, such services are a stop-gap, not a substitute for the scale needed to fund AI-heavy roadmaps. Strategically, the split creates a clear incentive for consolidation. Larger SaaS players will likely target niche AI-focused startups that have built specialized models but lack the infrastructure budget to scale. Acquisitions can instantly bolt AI capabilities onto robust, well-funded platforms, preserving the latter's growth trajectory while giving the acquired startup a runway. Conversely, cash-strapped firms may spin off AI-lite modules or pursue partnership models that share infrastructure costs. The net effect will be a more polarized SaaS ecosystem, where capital intensity becomes a primary determinant of market leadership. In the near term, operators should audit their AI spend against unit economics, prioritize telemetry that can surface intermittent performance issues, and consider fractional finance partners to keep runway intact. Investors, meanwhile, will need to sharpen diligence around AI cost structures, looking beyond headline ARR growth to the underlying cloud spend efficiency. The AI cloud-spending split is not just a budgeting issue - it is reshaping the competitive architecture of SaaS for the next decade.

Kalkine
Oct 15th, 2026
State Street prices $750M senior notes due 2037 with 5.963% fixed coupon

State Street Corporation priced a $750 million offering of fixed-to-floating rate senior notes due 2037, according to a filing on October 15, 2026. Settlement is expected on October 20, 2026. The notes pay a fixed 5.963% coupon, semi-annually, until October 20, 2036. After that, the rate becomes daily compounded SOFR plus 122 basis points. The issue price is 100% of principal, 88 basis points above the benchmark Treasury. State Street may redeem the notes in whole on October 20, 2036. Expected ratings are Aa3 from Moody's, A from S&P, and AA- from Fitch. Goldman Sachs, Morgan Stanley, Scotia Capital, and TD Securities are the joint book-running managers.

PR Newswire
Oct 14th, 2026
State Street shares fall 7% on $4.00B revenue miss as investors face securities probe

State Street shares fell about 7% at market open on October 14, 2026, after the company reported third-quarter revenue of $4.00 billion, below the roughly $4.03 billion analysts expected. Shares opened at about $161.90, down roughly $12.20 from the previous close. Fee revenue of about $3.14 billion also missed the estimated $3.18 billion. Law firm Levi & Korsinsky, through its SueWallSt service, has opened an investigation into whether State Street adequately disclosed fee-revenue trends before the report. It is also examining whether shareholders may have claims for potential securities law violations.

The Full FX
Oct 14th, 2026
State Street - Liquidity Insights 2026.

State Street - Liquidity Insights 2026. Posted by toast. Last updated: October 14, 2026 State Street's Liquidity Insights is a new dashboard offering real-time information in addition to what could be termed the standard range of analytical tools. What The Full FX really liked, however, is how, in addition to the volume, spread and depth data, it offers analysis on bespoke, multi-currency if required, baskets across a range of time horizons. The heat map offers fill rate per minute and reinforces the excellent look and feel to the platform, where finding and analysing information is easy. "What-if" analysis is supported by intuitive graphics, making it easy to ascertain current conditions compared to selected periods. An "at a glance" function completes the package. Ultimately, this launch fills a pressing gap for a giant in the real money space and given how some important clients in that arena like to have more of a say on their FX execution, it is delivering an important service from a familiar source. It is hard to offer something different in the execution analytics space, but allied to a strong presence in a key segment of the market, State Street has delivered a dashboard that just has a modern, intuitive and user-friendly feel.