Remote - LATAM

Employment Type: Full-Time

Compensation: Up to USD $8,500/month

About the Opportunity

We are looking for a Platform Engineer to build the platform that enables engineering teams to own software quality.

This is NOT a traditional QA role.

At our company, quality is owned by the engineers who write the code, with Product Managers sharing that ownership. You will not be the person responsible for testing features or approving releases. Instead, you will build the infrastructure, tooling, and developer experience that make it easy—and expected—for engineering teams to own quality themselves.

You will work across Software Engineering, Platform Engineering, Infrastructure, and Data Engineering to build scalable testing infrastructure, self-service environments, and production data quality tooling.

What You'll Do

Build and maintain testing infrastructure

• Build and maintain on-demand test environments in partnership with the Infrastructure team.
• Develop clone orchestration for Snowflake data warehouses and PostgreSQL application databases.
• Configure scoring engines, dbt pipelines, and Airflow workflows to run against cloned environments.
• Implement environment teardown, cost attribution, and access controls for production data used in test environments.

Build the testing platform

• Build and maintain the end-to-end testing framework and its CI/CD integrations.
• Create tooling that makes automated tests easy for engineering teams to write, execute, and maintain.
• Maintain the infrastructure supporting versioned seed datasets used for deterministic testing.

Improve production data quality

• Build infrastructure supporting production data monitoring.
• Implement pipeline idempotency checks.
• Build cardinality validations using dbt tests.
• Support distribution monitoring and automated alerting within data quality workflows.
• Create tooling that allows engineering teams to easily add new production data checks.

Improve developer experience

• Build tooling that makes test failures easy to diagnose through tracing, logs, and captured artifacts.
• Help engineers quickly determine whether failures originate from frontend, backend, data pipelines, or machine learning models.
• Continuously improve the reliability of the testing platform by identifying and eliminating flaky or intermittent tests.

Collaborate across engineering

• Partner with engineers and Product Managers to promote testing best practices.
• Maintain lightweight documentation, architecture notes, and operational runbooks.
• Evaluate emerging AI-assisted engineering and testing tools that improve developer productivity.
• Contribute to a collaborative, supportive engineering culture.

Must-Have

• Strong experience building testing infrastructure, developer tooling, or internal engineering platforms.
• Strong Python programming skills.
• Experience building CI/CD pipelines.
• Strong Docker experience.
• Experience with Snowflake, including zero-copy clones, warehouses, and cost controls.
• Strong SQL skills.
• Experience working with PostgreSQL.
• Experience implementing dbt tests.
• Experience provisioning infrastructure using Infrastructure as Code (IaC).
• Practical experience using AI coding tools to accelerate software development while maintaining engineering quality.
• Excellent written and spoken English communication skills.
• Comfortable working remotely with at least 6 hours of overlap with US Eastern Time.

Nice-to-Have Qualifications

• GitHub Actions at scale.
• End-to-end testing frameworks.
• Apache Airflow.
• Terraform, including the Snowflake Provider.
• Snowflake masking policies and access controls.
• Experience working with Clojure.
• Experience introducing testing practices that enable engineering teams without becoming a bottleneck.
• Experience maintaining AI agent skills, prompt libraries, or internal AI tooling.

Technical Environment

• Python
• Snowflake
• PostgreSQL
• SQL
• Docker
• dbt
• Airflow
• CI/CD
• GitHub Actions
• Infrastructure as Code (IaC)
• Terraform
• Clojure (Nice to Have)
• 
  

Working Style

We're looking for someone who enjoys building platforms that help other engineers succeed.

Success in this role comes from enabling engineering teams rather than becoming the person responsible for testing their software. You should enjoy creating scalable systems, improving developer workflows, asking thoughtful questions, collaborating across teams, and exercising sound engineering judgment.

We expect thoughtful use of AI tooling to accelerate development—not as a substitute for engineering judgment, testing, or peer review.

Interview Process

Our hiring process is designed to evaluate how you think, collaborate, and solve engineering problems.

There is no live coding and no take-home assignment.

Candidates who move forward will participate in a collaborative scenario-based discussion, similar to a pairing session, where they'll work through real engineering challenges such as designing testing infrastructure or production monitoring systems.

We evaluate:

• Engineering judgment
• Technical reasoning
• Collaboration
• Communication
• Quality of questions
• Ability to navigate ambiguity
• Mindset for enabling engineering teams rather than becoming a delivery bottleneck