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 ID*****
AgileEngine is an Inc. **** 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. **** 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.
#J-*****-Ljbffr

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