Platform Infrastructure Engineer

Bullish•New York, NY

2d•$150,000 - $185,000

About The Position

We are looking for a Platform Infrastructure Engineer to help build, run, and scale the Google Cloud Platform (GCP) foundation powering our high-performance trading exchange. In this role, you’ll work directly alongside senior engineers to design automated infrastructure, manage production Cloud, Kubernetes environments, and deliver developer-friendly tooling. This is an exceptional growth opportunity for an engineer who wants to master cloud-native infrastructure at scale, deepen their expertise in low-latency systems, and accelerate their career in the digital assets industry.

Requirements

Proven expertise in designing and managing cloud environments, including compute, storage, networking, and security components.
Solid working knowledge of containers and orchestration tools (Kubernetes, Docker, etc.) in production or staging environments.
Experience with infrastructure as code tools such as Terraform, CloudFormation, or similar.
Understanding of continuous integration/deployment platforms (e.g., GitHub Actions, GitLab CI, ArgoCD).
Understanding of networking fundamentals (VPCs, DNS, load balancers, firewalls).
Eagerness to learn, strong problem-solving skills, and a disciplined approach to reliability and security.
Effective communicator who thrives in a collaborative, fast-paced team environment.

Nice To Haves

Applicable cloud certifications, such as Google Cloud Professional Cloud Architect or AWS Certified Solutions Architect.
Ability to automate tasks using Python, Bash, or Go.
Exposure to financial technology, crypto systems, or high-volume web platforms.

Responsibilities

Execute Infrastructure as Code (IaC): Write, test, and deploy modular Terraform code to provision safe, repeatable cloud environments on GCP and other cloud providers.
Support Production Kubernetes: Maintain and optimize Google Kubernetes Engine (GKE) clusters, supporting containerized services with focus on uptime, networking, and scaling.
Integrate and utilize AI-powered tools to enhance platform operations: Apply LLM-based coding assistants to accelerate infrastructure provisioning and debugging. As well as managing and improving the AI platform used by all teams.
Enhance CI/CD & Developer Experience: Collaborate with application development teams to streamline CI/CD pipelines and accelerate code deployments to production.
Troubleshoot & Respond: Participate in incident response, dig into root causes alongside senior team members, and build long-term fixes to prevent recurrence.
Optimize Cloud Resources & Cost Efficiency: Balance cloud spend with high performance, scaling efficiency, and strict security standards.
Drive Cross-Functional Collaboration: Work closely with development, operations, and security teams to define robust cloud architecture and champion industry best practices.
Expand Developer Self-Service (Backstage IDP): Build and enhance our Backstage internal developer portal to streamline workflows and boost productivity across all engineering teams.