Remote Gpu Infra Engineer

The Role: We are looking for an Infrastructure / DevOps Engineer to join our Cloud Platform Engineering Team.

In this role, you will own cloud infrastructure, deployment automation, and system reliability , with a strong focus on cloud-agnostic portability, Kubernetes administration, Infrastructure as Code, and automated CI/CD workflows.

We are looking for someone with strong hands-on experience in Kubernetes, Terraform, GitHub Actions, multi-cloud environments, and IAM solutions such as Keycloak .

Responsibilities:

• Kubernetes Administration: Deploy, manage, scale, and troubleshoot workloads on Kubernetes, initially using Google Kubernetes Engine (GKE), with Helm and Kustomize.
• Infrastructure as Code: Build modular and cloud-agnostic infrastructure using Terraform, enabling consistent deployments across GCP, other public clouds, and on-premise environments.
• CI/CD Pipeline Ownership: Design, maintain, and optimize reusable GitHub Actions workflows for automated testing, containerization, and deployment.
• Manage container images and deployment workflows using GitHub Container Registry (GHCR).
• IAM & Platform Deployment: Deploy, operate, and scale highly available Keycloak clusters.
• Configure GitHub Workload Identity Federation (OIDC) to provide GitHub Actions with secure, keyless access to GCP resources.
• Implement and maintain secure secrets management practices.
• Collaborate with technical leadership to evaluate and improve deployment strategies, including traditional CI/CD and GitOps approaches using tools such as ArgoCD or Flux.
• Contribute to the reliability, scalability, security, and portability of the overall cloud platform.

Requirements:

• Advanced hands-on experience managing production Kubernetes environments, including container networking.
• Strong proficiency with Terraform, Helm, and Infrastructure as Code (IaC) methodologies.
• Deep experience designing and maintaining deployment pipelines using GitHub Actions.
• Experience working with GitHub Container Registry (GHCR).
• Experience deploying and maintaining production Keycloak/IAM environments.
• Strong understanding of OIDC, identity management, authentication, and authorization concepts.
• Experience with secrets management and cloud security best practices.
• Experience working with GCP/GKE and an understanding of multi-cloud or cloud-agnostic infrastructure approaches.
• Strong understanding of containerized environments, deployment automation, and system reliability

Core Tech Stack

Kubernetes (GKE) | Terraform | Helm | Kustomize | GitHub Actions | GHCR | GCP | Multi-Cloud | Keycloak | OIDC | IaC | ArgoCD / Flux

Data Engineering & Infrastructure Lead ID88014

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you :)

ABOUT THE ROLE

We are looking for a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL pipeline decisions in an advisory capacity. This person weighs managed tooling against custom builds, reviews SageMaker-based MLOps pipelines, and mentors the team on engineering standards. Evaluating AI-assisted development workflows is part of the role.

WHAT YOU WILL DO

• Audit the current AWS architecture across live applications (MAT / Signal IQ and the Impact Engine), including ECS/ECR, RDS (Postgres), S3, VPC, CloudFront/SSO, and SageMaker-based MLOps pipeline design.
• Review the CI/CD process and end-to-end app development lifecycle, recommending SDLC governance layers (schema versioning, environment separation, release gating).
• Evaluate how the team uses Claude Code (PR generation, automated reviews, token/cost management) to confirm output meets professional engineering standards.
• Provide an early technical opinion on ETL / data-ingestion pipeline architecture (managed ELT tooling vs. custom build).
• Mentor and accelerate the day-to-day infrastructure build team, focusing on AWS, DevOps, CI/CD, and data engineering practices.
• Set out recommendations and technical direction where the audit surfaces necessary changes to the current build.
• Report findings and recommendations directly to leadership, framing high-level risk and readiness.

MUST HAVES

• 6+ years of deep, current hands-on experience with AWS: ECS/Fargate,