Infrastructure Engineer - Gauntlet

About the role

This Infrastructure Engineer role at Gauntlet focuses on building and maintaining the core infrastructure that powers its onchain finance products. The position involves supporting application teams by fulfilling infrastructure requests, owning and extending CI/CD processes, and managing Kubernetes deployments. A key aspect of the work will be to ensure fully automated and secure deployments, minimizing direct engineer access to production environments.

The successful candidate will be responsible for authoring and updating Terraform modules across GCP environments, ensuring infrastructure is managed as code. They will also play a critical role in unifying observability across the platform, consolidating alerting systems into a single view for better incident management. This includes routing failures to the correct teams and on-call rotations.

A significant part of the role involves advancing the resilience and security of Gauntlet's infrastructure. This means working towards cloud-agnostic services, applying robust IAM and secrets management practices, and contributing to SOC 2 readiness. The position also involves automating routine tasks using AI, allowing engineers to focus on more complex challenges.

The national pay range for this role is between $150,000 and $175,000 annually, plus potential additional on-target earnings and company equity.

Skills that matter here

• GCP: This role requires hands-on experience with Google Cloud Platform, as it is the primary cloud environment for Gauntlet's infrastructure.
• Kubernetes: The engineer will be responsible for running and managing large-scale Kubernetes production systems, including service deployments via Helm.
• Terraform: Infrastructure as Code is central to this role, with a focus on authoring and updating Terraform modules for new and existing services.
• GitHub Actions: The position involves maintaining and extending existing GitHub Actions workflows and potentially migrating towards a dedicated CD tool.
• Python: Strong software engineering fundamentals in Python are highly valued, along with comfort in scripting and shell environments.
• Dagster: The role includes managing and ensuring the health of async workloads running on Dagster within the Kubernetes environment.

Who this role suits

• A person who thrives on building robust, secure, and automated infrastructure.
• Someone with a strong background in cloud-native platforms, particularly GCP and Kubernetes.
• An individual who values clear written communication for incident reports and design decisions.
• A candidate who is comfortable debugging complex production issues using various tools and source code.

From the employer

• Support the application teams: turn around infra requests (permissions, roles, service setup, project peering) so product engineers stay focused on shipping.
• Own CI/CD and deployments: maintain and extend our GitHub Actions workflows and help migrate toward a dedicated CD tool with proper permissioning — the goal is fully automated, locked-down deploys via service accounts, no direct engineer access to production.
• Build and maintain infrastructure as code: author and update Terraform modules for new and existing services across GCP environments.
• Run Kubernetes the right way: manage service deployments via Helm (we're on Helm 4) keep async workloads healthy on Dagster.
• Unify observability (likely first project): consolidate today's per-team alerting into a single view — system-to-system dashboards plus incident alerting that routes upstream service/vendor failures to the right impacted teams and on-call rotations.
• Advance resilience: help move us toward a fully region- and cloud-agnostic posture so services can pick up and move if something fails.
• Strengthen security & access: apply IAM, secrets management, least privilege, and auditability; contribute to SOC 2 readiness.
• Automate with AI: build agent skills / `agents.md` so routine tasks (provisioning access, simple changes) can be handled by an agent instead of human engineering hours, and use AI to reason through bigger problems.

• Strong software-engineering fundamentals in at least one production language (Python, Go, TypeScript, or Rust); Python especially valued, plus comfort scripting and working in the shell.
• Hands-on experience with cloud infrastructure and core cloud services, especially GCP (AWS/Azure transferable).
• Experience operating large-scale Kubernetes production systems.
• Experience with Infrastructure as Code, especially Terraform.
• Familiarity with CI/CD systems, especially GitHub Actions or Octopus Deploy.
• Ability to debug production issues using logs, metrics, traces, shell tools, and source code.
• Security and access-control fundamentals: IAM, secrets management, least privilege, and auditability.
• Clear written communication around incidents, design decisions, and operational procedures.

• The national pay range for this role is $150,000 - $175,000 base plus additional On Target Earnings potential by level and equity in the company.
• Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide.
• Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.