Staff Security Engineer, Cloud & AI Platform

Brookfield Real Estate Group is a global real estate investment and operating business within Brookfield. The Staff Security Engineer, Cloud & AI Platform will lead hands-on security architecture and implementation across AWS, infrastructure as code, software delivery, internally developed applications, and AI systems. The role focuses on building reusable security controls, threat modeling, secure engineering patterns, detection capabilities, and assurance mechanisms in partnership with engineering, identity, CyberOps, and GRC/Privacy teams.

Responsibilities:

• Help define security architecture for the cloud and AI platforms: set direction, write specs, and steward secure-by-default patterns across teams
• Define security engineering standards and paved roads, document important decisions, and communicate risk and trade-offs to engineering and business leadership
• Review infrastructure and application designs for authorization, network, data-protection, secrets, and tenant-isolation risks
• Mentor engineers and raise the organization’s ability to make sound security decisions independently
• Partner with Cloud Solutions, application engineering, AI engineering, Identity, CyberOps, and GRC/Privacy to prioritize work and drive adoption
• Own and evolve security architecture for a multi-account AWS organization — account boundaries, service control policies, IAM Identity Center, delegated security services, KMS, VPC controls, and WAF
• Design least-privilege human and workload access across AWS, Okta, GitHub Actions, and Infrastructure as Code platforms using federation and short-lived credentials
• Build and maintain reusable security controls in Terraform or OpenTofu, with safe rollout, testing, monitoring, and recovery patterns
• Strengthen centralized logging and evidence — CloudTrail, Config, GuardDuty, Security Hub, Macie, and CloudWatch — and keep guardrails current as the environment grows
• Establish secure GitHub Actions and runner patterns, including OIDC trust, environment separation, workflow protection, action pinning, artifact integrity, and least-privilege deployment roles
• Integrate practical security checks into developer workflows — secrets detection, dependency and container scanning, SBOMs, Infrastructure as Code analysis, code scanning, and risk-based release gates
• Support vulnerability management for internally developed software, from detection and prioritization through remediation evidence and exception handling. Partner with the Vulnerability Manager to establish prioritization and reduce false positives
• Improve controls with engineers rather than around them, avoiding noisy or easily bypassed gates
• Lead threat modeling and security design reviews for web applications, APIs, data ingestion, authentication and authorization flows, and agentic systems
• Define secure patterns for Amazon Bedrock and other model platforms, including model access, guardrail lifecycle, invocation logging, usage attribution, and sensitive-data controls
• Harden agent tools, MCP servers, gateways, sandboxes, and code-execution environments against prompt injection, confused-deputy attacks, excessive agency, secret disclosure, data exfiltration, and cross-tenant access
• Build repeatable security evaluations and adversarial tests for AI-enabled features and connect findings to engineering remediation
• Translate cloud and application telemetry into actionable detections, runbooks, ownership, and escalation paths in partnership with CyberOps
• Lead technical response and root-cause remediation for cloud, identity, software supply chain, and AI security incidents
• Establish severity and ownership standards for cloud findings, software vulnerabilities, and AI security issues, with clear remediation expectations
• Produce the control evidence GRC and Privacy need, without turning engineering work into manual reporting

Requirements:

• 8+ years Experience
• Demonstrated senior or Staff-level ownership of production security or platform systems, including architecture decisions others build on
• Deep AWS security experience across IAM, multi-account or AWS Organizations environments, logging and detection, KMS, networking, and service-to-service authorization
• Strong Terraform or OpenTofu skills, including modular design, remote execution, policy controls, and safe state-aware changes
• Experience securing CI/CD systems such as GitHub Actions, including OIDC federation, runner trust boundaries, secrets, artifacts, and deployment permissions
• Working knowledge of application security fundamentals: threat modeling, authentication and authorization, secure API design, secrets handling, dependency risk, and vulnerability remediation
• Ability to read and write production-quality automation or application code in Python, Go, Ruby, or a comparable language
• Demonstrated ability to influence teams you do not manage, make pragmatic risk decisions, and turn ambiguous security needs into implemented controls
• Experience with Amazon Bedrock, AgentCore, MCP, LLM gateways, AI guardrails, or production agentic systems
• Container and orchestration security — ECS/Fargate or EKS, image supply chains, runtime isolation, and egress control
• Identity platform depth: IAM Identity Center, Okta, Delinea, SAML, OIDC, OAuth, SCIM, ABAC, and enterprise entitlement systems
• Experience with Scalr, Terraform Cloud, or another remote Infrastructure as Code platform
• Familiarity with CrowdStrike Falcon Cloud Security, Datadog, CloudWatch, or comparable security and observability tooling
• Data platform and sensitive-data controls involving S3, Snowflake, PostgreSQL/Aurora, or vendor data ingestion
• AI threat modeling, red teaming, or security evaluation experience