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, ECR, RDS (Postgres), S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM.
- Fluency in Infrastructure-as-code, specifically Terraform.
- Proven track record designing or auditing CI/CD pipelines and SDLC governance (e.g., Alembic for schema/version control, environment separation, release gating).
- Strong data engineering depth to provide defensible opinions on ETL / ingestion architecture (managed tools vs. custom builds).
- Experience evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) from an engineering-quality and cost-governance standpoint.
- Comfortable operating in a part-time advisory capacity (50% stepping down to 25%) as a strong communicator who can mentor less experienced engineers.
NICE TO HAVES
- Prior experience working with small, fast-moving engineering teams.
- Understanding of MLOps pipelines and data science infrastructure.
- Media/AdTech domain knowledge is helpful but not required.
PERKS AND BENEFITS
- Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Job Description
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, ECR, RDS (Postgres), S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM.
- Fluency in Infrastructure-as-code, specifically Terraform.
- Proven track record designing or auditing CI/CD pipelines and SDLC governance (e.g., Alembic for schema/version control, environment separation, release gating).
- Strong data engineering depth to provide defensible opinions on ETL / ingestion architecture (managed tools vs. custom builds).
- Experience evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) from an engineering-quality and cost-governance standpoint.
- Comfortable operating in a part-time advisory capacity (50% stepping down to 25%) as a strong communicator who can mentor less experienced engineers.
- Upper-intermediate English level.
NICE TO HAVES
- Prior experience working with small, fast-moving engineering teams.
- Understanding of MLOps pipelines and data science infrastructure.
- Media/AdTech domain knowledge is helpful but not required.
PERKS AND BENEFITS
- Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.
Requirements
- 6+ years of deep, current hands-on experience with AWS: ECS/Fargate, ECR, RDS (Postgres), S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM.
- Fluency in Infrastructure-as-code, specifically Terraform.
- Proven track record designing or auditing CI/CD pipelines and SDLC governance (e.g., Alembic for schema/version control, environment separation, release gating).
- Strong data engineering depth to provide defensible opinions on ETL / ingestion architecture (managed tools vs. custom builds).
- Experience evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) from an engineering-quality and cost-governance standpoint.
- Comfortable operating in a part-time advisory capacity (50% stepping down to 25%) as a strong communicator who can mentor less experienced engineers.