Part-Time AWS Data & Infra Lead (MLOps & SDLC)

Mapfre; Buenos Aires; Hybrid; ARS 90,873,000 - 181,747,000; Part time

Benefits offered by this job

Flextime

Work-from-home option

Competitive USD compensation

Mentorship and growth opportunities

Job summary

AgileEngine seeks a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL pipeline decisions in an advisory capacity. The role weighs managed tooling against custom builds and mentors the team on engineering standards, including evaluating AI-assisted workflows.

The position emphasizes Terraform IaC, SDLC governance, and data engineering depth to address ETL and ingestion architecture while guiding cost governance of AI-assisted development.

Qualifications

• 6+ years of AWS hands-on experience (ECS/Fargate, RDS Postgres, S3, SageMaker)
• Fluency in Terraform IaC
• Proven track record designing or auditing CI/CD pipelines and SDLC governance
• Strong data engineering depth for ETL/ingestion architecture
• Experience evaluating AI-assisted development workflows (Claude Code)
• Part-time advisory capacity and mentoring engineers

Responsibilities

• Audit the current AWS architecture across live applications (ECS/ECR, RDS, S3, VPC, CloudFront/SSO, SageMaker-based MLOps)
• Review the CI/CD process and end-to-end app development lifecycle; recommend SDLC governance layers
• Evaluate Claude Code usage for output quality and cost governance
• Provide opinions on ETL/ingestion pipeline architecture (ELT tooling vs. custom)
• Mentor and accelerate the day-to-day infrastructure build team (AWS, DevOps, CI/CD, data engineering)
• Set recommendations and technical direction after audits
• Report findings and recommendations to leadership with risk framing

Skills

AWS architecture

CI/CD pipelines

SDLC governance

Mentoring

Communication

Tools

Terraform

SageMaker

Claude Code

Job description

AgileEngine seeks a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL pipeline decisions in an advisory capacity. The role weighs managed tooling against custom builds and mentors the team on engineering standards, including evaluating AI-assisted workflows.

The position emphasizes Terraform IaC, SDLC governance, and data engineering depth to address ETL and ingestion architecture while guiding cost governance of AI-assisted development.