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We are looking for a platform infrastructure engineer to design, build, and operate cloud-native infrastructure for deploying AI workloads safely and reliably at scale.
AI systems — including autonomous agents, model-serving pipelines, and long-running inference workloads — present unique infrastructure challenges: multi-tenant isolation, network security, container lifecycle management, and operational resilience. This role owns the Kubernetes platform layer that makes safe cloud deployment of these workloads possible.
The engineer will design container architectures for security-sensitive and multi-tenant environments, implement network policies and access controls for workload isolation, build CI/CD pipelines for reliable deployment, and establish infrastructure-as-code practices for reproducibility and auditability. They will work closely with AI engineers but their primary focus is the platform itself — making it secure, scalable, and operationally excellent.
Beyond immediate needs, they will help establish platform infrastructure best practices that can be applied across the firm's broader cloud-native footprint.
Qualifications
- 5+ in a platform/infrastructure/DevOps engineering role
- Bachelor’s degree in Computer Science or a related field
- Deep hands-on experience with Kubernetes (EKS preferred) — cluster design, networking (CNI, service mesh), RBAC, and security policies
- Strong AWS expertise — VPC architecture, IAM, ECS/EKS, networking, and security groups
- Proficiency with Infrastructure-as-Code tools such as Terraform, CloudFormation, or Pulumi
- Experience designing container architectures for multi-tenant or security-sensitive workloads
- Familiarity with GitOps workflows and CI/CD platforms (ArgoCD, GitHub Actions, Jenkins)
- Python and/or Go for tooling and automation
- Technical leadership — ability to drive architectural decisions and mentor others
- Desire to deliver cutting edge infrastructure in a fast-moving environment
- Stay up-to-date with the latest advancements in cloud-native infrastructure, container security, and AI workload deployment
Nice to have
- Familiarity with AI infrastructure —agent orchestration frameworks, MCP
- InfoSec familiarity using Sandboxing and setting policies with REGO, OPA, etc.
- Experience in the financial domain — regulated environments, compliance-aware infrastructure
- Experience with container orchestration platforms for autonomous or long-running AI workloads
- Prior experience securing production AI agent workloads at scale
The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. When finalizing an offer, we take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.
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