Senior Cloud Engineer (AWS / Azure / GCP) - VP

Morgan Stanley; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Morgan Stanley is looking for a Senior Cloud Engineer / Site Reliability Engineer in New York to design and operate secure, scalable cloud platforms across AWS, Azure, and GCP. The role involves building cloud infrastructure, deploying virtual machines, and leading high-stakes production deployments. Candidates should have over 10 years of experience in cloud engineering, strong Terraform and Kubernetes skills, and expertise in incident response. The expected salary ranges from $150,000 to $210,000 annually.

Qualifications

• 10+ years in cloud engineering, platform engineering, DevOps, or SRE roles.
• Strong hands-on experience across AWS, Azure, and GCP.
• Expert-level in Terraform and Kubernetes operations.

Responsibilities

• Design, build, and operate secure cloud platforms across AWS, Azure, and GCP.
• Lead incident response for technical escalations.
• Define and improve SLIs/SLOs for critical services.

Skills

Cloud engineering

Terraform

Kubernetes operations

Incident response

Linux

Scripting (Bash/Python)

Security fundamentals

Tools

AWS

Azure

GCP

Job description

Role Summary

We are seeking a Senior Cloud Engineer / Site Reliability Engineer (SRE) to design, build, and operate secure, scalable cloud platforms across AWS, Azure, and GCP. This role is responsible for configuring, deploying, and maintaining virtual machines and containerized applications, using Terraform to automate infrastructure provisioning and lifecycle management. You will provide specialized support for high‑stakes production deployments, lead incident response for technical escalations, and apply SRE principles (SLIs/SLOs, error budgets, automation, and reliability engineering) to improve availability, performance, and operational excellence in a multi‑cloud environment.

Key Responsibilities

Cloud Platform Engineering (AWS / Azure / GCP)

• Architect, implement, and maintain cloud infrastructure across AWS, Azure, and GCP using Terraform (IaC).
• Design and implement cloud landing zones aligned with best practices:
  • Account/subscription/project structure, environment separation, identity boundaries
  • Baseline guardrails and policy enforcement (Azure Policy, AWS Organizations/SCPs, GCP Org Policies)
  • Centralized audit logging, monitoring, and cost allocation standards
• Build and operate cloud‑native virtual network constructs (cloud‑focused only):
  • Azure: VNETs, subnets, NSGs, route tables, Private Endpoints, hub/spoke patterns.
  • AWS: VPCs, subnets, security groups, NACLs, route tables, VPC endpoints/PrivateLink, multi‑account connectivity patterns.
  • GCP: VPC networks, subnets, firewall rules, routes, Private Service Connect, Shared VPC patterns.
• Implement private‑by‑default service access patterns (private endpoints, controlled egress, service‑to‑service access controls).

Compute, Virtual Machines, and Containers

• Configure, deploy, and maintain virtual machines and scalable compute patterns:
  • AWS EC2 (Launch Templates, Auto Scaling Groups)
  • Azure Virtual Machines / VM Scale Sets
  • GCP Compute Engine / Managed Instance Groups
• Own OS hardening, baseline configuration, patching strategies, and instance bootstrapping (cloud‑init, image pipelines).
• Deploy and operate containerized workloads using Kubernetes:
  • EKS / AKS / GKE (cluster design, upgrades, node pools, RBAC, scaling)
  • Container registries (ECR / ACR / Artifact Registry) and artifact promotion strategies
• Implement workload delivery patterns (Helm/Kustomize), rollout strategies (blue/green, canary), and safe rollbacks.

Infrastructure as Code, Automation & CI/CD (Terraform)

• Build reusable, versioned Terraform modules with standards for naming, tagging/labels, and secure defaults.
• Implement Terraform best practices: remote state, locking, environment isolation, secrets handling, and drift detection.
• Integrate IaC into CI/CD pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI):
  • Automated validation, linting, security scanning, plan/apply workflows, approvals, and promotions
• Implement policy‑as‑code guardrails (OPA/Conftest, Sentinel where applicable) to prevent unsafe changes.

SRE: Reliability Engineering, Observability & Operational Excellence

• Define, implement, and improve SLIs/SLOs (availability, latency, error rates, saturation) for critical services and platforms.
• Manage and enforce error budgets to balance reliability with delivery velocity.
• Establish and continuously improve observability standards:
  • Metrics, logs, traces, dashboards, and alerting across cloud services and Kubernetes
  • Tooling such as CloudWatch, Azure Monitor/Log Analytics, GCP Cloud Monitoring/Logging, OpenTelemetry, Prometheus/Grafana (where used)
• Improve incident detection quality by reducing alert noise, implementing actionable alerts, and creating clear escalation paths.
• Drive reliability improvements through:
  • Capacity planning, performance tuning, load testing support
  • Resilience engineering (multi‑zone design, graceful degradation, retries/timeouts, backpressure)
  • Continuous automation to eliminate toil (self‑healing, auto‑remediation runbooks, ChatOps where applicable)

Production Support, Incident Response & Escalations

• Provide specialized support for high‑stakes production deployments (major releases, platform cutovers, migrations).
• Lead incident response: triage, mitigation, recovery, communication, and post‑incident review (PIR/RCA).
• Troubleshoot escalations across cloud services, Kubernetes, IAM, storage, and CI/CD pipelines using evidence‑driven debugging.
• Build and maintain runbooks, operational playbooks, and postmortem action tracking to prevent repeat incidents.
• Participate in on‑call rotation and continuously improve on‑call health through automation and better observability.

Security, Identity, and Governance

• Implement least‑privilege access controls across AWS/Azure/GCP (IAM/RBAC), including role design and permission boundaries.
• Enforce secure configurations: encryption at rest/in transit, secrets management, key management (KMS/Key Vault/Cloud KMS).
• Implement compliance‑oriented logging and auditing, and partner with security teams to remediate findings and harden platforms.

Required Skills & Experience

• 10+ years in cloud engineering, platform engineering, DevOps, or SRE roles with significant production ownership.
• Strong hands‑on experience across AWS and Azure, plus practical experience in GCP (production exposure preferred).
• Expert‑level Terraform (modules, state, CI integration, scalable environment patterns).
• Strong Kubernetes operations experience (EKS/AKS/GKE), including upgrades, scaling, and workload reliability.
• Experience implementing SRE practices: SLIs/SLOs, alerting strategies, incident response, post‑mortems, and automation/toil reduction.
• Strong Linux and scripting (Bash/Python) and ability to debug systems from symptoms to root cause.
• Strong security fundamentals: IAM/RBAC, encryption, secrets, and auditability in cloud environments.
• Proven ability to lead technical escalations and coordinate resolution across teams.

Compensation

Expected base pay rates for the role will be between $150,000 and $210,000 per year at the commencement of employment. Base pay will be determined on an individualized basis and is only part of the total compensation package, which may also include commission earnings, incentive compensation, discretionary bonuses, other short and long‑term incentive packages, and other sponsored benefit programs.

EEO Statement

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents. Our workforce reflects a broad cross‑section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.