Part-Time AWS Data & Infra Lead for ML/ETL & CI/CD

Capgemini Engineering; Buenos Aires; Hybrid; ARS 182,771,000 - 243,694,000; Part time

Benefits offered by this job

Professional growth

Competitive USD compensation

A selection of exciting projects

Flextime

Job summary

AgileEngine is seeking a part‑time Data Engineering and Infrastructure Lead to audit AWS architecture and CI/CD processes, mentoring the team on standards. You will review SageMaker ML pipelines, tool choices, and ETL architecture while advising leadership on risk and readiness.

In this advisory role (50% to 25%), you’ll shape governance, environment separation, and release gating, ensuring scalable, cost‑efficient engineering practices for modern AI‑driven projects.

Qualifications

• 6+ years of hands‑on AWS experience with ECS/Fargate, ECR, RDS Postgres, S3, SageMaker and IAM.
• Fluency with Infrastructure‑as‑code using Terraform.
• Proven track record auditing CI/CD pipelines and SDLC governance.
• Strong data engineering depth for ETL/ingestion architecture opinions.
• Experience evaluating AI-assisted development workflows and cost governance.
• Part‑time advisory capacity (50% down to 25%) and clear mentoring ability.

Responsibilities

• Audit AWS architecture across live apps and SageMaker‑based ML pipelines.
• Review CI/CD and governance, recommending environment separation and release gates.
• Evaluate Claude Code usage for quality and cost control.
• Advise on ETL/data‑ingestion architecture between managed ELT and custom builds.
• Mentor infrastructure build team on AWS, DevOps, and data engineering best practices.
• Set directions and report findings to leadership with risk and readiness framing.

Skills

AWS

Terraform

CI/CD

SDLC governance

Data engineering

LLM tooling

Tools

SageMaker

ECS/Fargate

ECR

RDS Postgres

S3

IAM

EventBridge

Job description

AgileEngine is seeking a part‑time Data Engineering and Infrastructure Lead to audit AWS architecture and CI/CD processes, mentoring the team on standards. You will review SageMaker ML pipelines, tool choices, and ETL architecture while advising leadership on risk and readiness.

In this advisory role (50% to 25%), you’ll shape governance, environment separation, and release gating, ensuring scalable, cost‑efficient engineering practices for modern AI‑driven projects.