Location

Brookfield Place New York - 225 Liberty Street, 8th Floor

Our Company

At Brookfield Real Estate, the foundation of our success is firmly rooted in our people. Our company is comprised of experts across a range of specialties who share a goal of ensuring our properties continuously evolve to meet the needs of our communities and stakeholders. We hire visionary, entrepreneurial talent who help us innovate and enhance our business, building collaborative teams who value integrity, creativity, and diversity.

Our teams operate an iconic portfolio of irreplaceable properties within the world’s most dynamic markets. As one of the largest real estate services companies, we provide management and development expertise exclusively for properties owned by Brookfield Asset Management.

The Lead DevOps Engineer is a deeply technical role responsible for building the foundational infrastructure powering Brookfield Real Estate’ strategic initiative. Specializing in AWS, you will work cross-functionally with AI and ML development teams to design, architect, deploy, and maintain the cloud infrastructure powering our AI-native platforms. Brookfield Real Estate is on a mission to become the most AI-Enabled Real Estate Team.

A successful engineer brings a DevOps mindset to platform management, working closely with the development, product, and leadership teams to effectuate scalable, reliable, and secure systems.

The engineer will be part of the Cloud Solutions team, which supports internally developed applications across AWS, GCP, and Azure. This position focuses on AWS. Candidates should be comfortable contributing across multiple roles in the application stack.

Responsibilities

Leadership

- Act as the technical owner of the AI platform: drive architecture decisions, write specs, and steward best practices throughout the organization.

- Work closely with product and engineering leadership to ensure infrastructure architecture satisfies the problem at hand.

- Regularly attend standup and Agile ceremonies.





- Pair with senior application engineers to ensure platform constraints and product needs converge early; mentor more junior engineers across both repos on cloud, container, and IaC fundamentals.

- Communicate technical trade-offs (cost, security, reliability, velocity) to product and engineering leadership.

Platform Engineering
- Own the AWS infrastructure for hosted web applications powering Brookfield Real Estate’s AI initiatives.

- Manage and improve the GitHub pipelines to reduce developer friction, further automate deployments (blue/green), and work towards high availability and disaster recovery.

- Operate the application, ML and LLM observability infrastructure – Langfuse, OpenTelemetry, Cloudwatch, Datadog.

- Contribute at a lead level to the companies Infrastructure as Code efforts utilizing a Terraform-first mindset.

- Build serverless components for the platform — Lambda, API Gateway, Step Functions, EventBridge, SQS/SNS, SES.

AI/ML Platform Support
- Partner with the AI application engineers to architect and operate agentic systems built on tools such as LangChain, LangGraph, or Claude Code SDK.

- Effectively utilize AI as a force multiplier for engineering work to produce high-quality artifacts.

- Enhance the applications capabilities by integrating custom tools and agents via AWS AgentCore Gateway.

- Expand the integration with Bedrock and other inference tooling.

- Secure and improve sandboxing for agentic processes.

- Own the strategy and evolution of the organization’s knowledge base, aligning it with agentic system capabilities and product needs.

- Improve evaluation pipelines, develop a scalable architecture for prompt evaluation tuning.





Operations, Security & Reliability
- Debug across the stack — Linux containers, Python services, Aurora performance, Redis OOM, ECS task placement, ALB health checks, CloudFront/WAF rules, and Terraform/Scalr state issues.

- Secure the platform with defense in depth.

- Own production reliability for the Labs application — availability, latency, and capacity SLOs — through proactive monitoring, alerting, and runbooks.

Qualifications

- 9+ years in DevOps, cloud platform engineering, or SRE roles, with at least 2 years owning a production platform end-to-end.

- Strong Python — comfortable writing and debugging FastAPI/Lambda code.

- Deep expertise in AWS ECS/Fargate in production. EKS experience is beneficial but not required for this role.

- Strong serverless: Lambda, API Gateway, Step Functions, EventBridge, SQS/SNS, SES.

- Robust knowledge of core AWS services: VPC (private subnets, NAT, VPC endpoints), IAM, S3, Secrets Manager, CloudWatch, ALB, CloudFront, WAF, Route53, ACM, RDS/Aurora).

- Infrastructure-as-Code with OpenTofu or Terraform, including modular design and remote backends (Scalr/HCP/TFC).

- CI/CD with GitHub Actions.

- Container engineering: Docker image design, multi-arch builds, image hardening, layer caching.

- Security: least-privilege IAM, OIDC, WAF rule design, secret handling, sandbox isolation patterns.

Nice to Have
- Hands-on experience operating agentic AI / LLM workloads in production (Bedrock, Langfuse, LangGraph/LangChain, MCP servers, model invocation cost tracking).

- Familiarity with Snowflake Cortex or other warehouse-native AI features.

- Experience operating in a DevOps adjacent role (software engineering, ML, Data Science).

- Multi-cloud experience (GCP, Azure)

We are proud to create a diverse environment and are proud to be an equal opportunity employer. We are grateful for your interest in this position, however, only candidates selected for pre-screening will be contacted.

📌 Lead DevOps Engineer (Canada)
🏢 USA II
📍 Canada