Application Guide

How to Apply for Senior Cloud Quality Assurance Automation Engineer

at Hayden AI

🏢 About Hayden AI

Hayden AI develops AI-driven solutions specifically for urban mobility and transit safety, focusing on making cities more sustainable and efficient. Unlike generic tech companies, they apply computer vision and AI directly to real-world transportation challenges, offering a mission-driven environment where technology has tangible social impact. Working here means contributing to safer streets and smarter cities through innovative cloud and data solutions.

About This Role

This Senior Cloud QA Automation Engineer role involves designing and maintaining automated test suites for Hayden AI's entire cloud ecosystem, including AWS microservices, data pipelines, and frontend applications. You'll ensure data integrity across InfluxDB and Redshift while building dashboards in Grafana/Datadog to monitor system health and KPIs. Your work directly impacts the reliability of AI-driven transit solutions that cities depend on for safety and efficiency.

💡 A Day in the Life

You might start by reviewing automated test results from overnight runs on AWS data pipelines, then write new Pytest scripts for API ingestion flows. After standup, you could optimize SQL queries to validate KPIs in Redshift, then update Grafana dashboards to track system performance trends. Later, you'd integrate new tests into the Jenkins CI/CD pipeline and collaborate with data engineers on ETL workflow validation.

🚀 Application Tools

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Interview Prep

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🎯 Who Hayden AI Is Looking For

  • Has 7+ years specifically in cloud/SaaS QA automation with hands-on experience testing AWS components like Glue, Lambda, S3, and Redshift data pipelines
  • Demonstrates strong Python/Pytest or Java/TestNG skills for building automation frameworks, plus SQL optimization for validating time-series data in InfluxDB
  • Has integrated automated tests with CI/CD tools like Jenkins or GitHub Actions and can show experience with REST API testing using Postman or similar tools
  • Can create and maintain operational dashboards in Grafana and Datadog for monitoring and alerting in production environments

📝 Tips for Applying to Hayden AI

1

Highlight specific projects where you automated testing for AWS data pipelines (Glue, Lambda, S3, Redshift) - quantify results like test coverage improvements or bug detection rates

2

Showcase your experience with both InfluxDB (time-series) and Redshift (data warehouse) validation in your resume, including SQL query optimization examples

3

Demonstrate how you've integrated QA automation into CI/CD pipelines - mention specific tools like Jenkins or GitHub Actions and the impact on deployment frequency

4

Include examples of Grafana or Datadog dashboards you've built for monitoring and alerting, explaining what metrics you tracked and why

5

Tailor your application to mention Hayden AI's urban mobility focus - show how your QA experience ensures reliability for mission-critical transit systems

✉️ What to Emphasize in Your Cover Letter

['Your experience with end-to-end test automation for cloud-based microservices and data pipelines, specifically mentioning AWS components like Glue and Lambda', "How you've validated data integrity across different database systems (InfluxDB for time-series, Redshift for analytics) and optimized SQL queries for performance", 'Examples of integrating automated tests into CI/CD pipelines and building monitoring dashboards that improved system reliability', "Why you're drawn to Hayden AI's mission of safer, more sustainable urban transit and how your QA expertise supports that goal"]

Generate Cover Letter →

🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Hayden AI's specific products like their automated bus lane enforcement or transit signal priority systems to understand what you'll be testing
  • → Their technology blog or case studies to see how they use AWS, data pipelines, and monitoring in real deployments
  • → Urban mobility challenges in San Francisco and other cities they serve to understand the context of their solutions
  • → Their engineering culture through Glassdoor or LinkedIn to understand their development and testing practices

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk me through how you would design an automated test suite for an AWS data pipeline involving Glue, Lambda, and Redshift
2 How do you validate data accuracy when moving between InfluxDB (time-series) and Redshift (data warehouse) systems?
3 Describe your experience building and maintaining Grafana/Datadog dashboards - what KPIs do you monitor for cloud-based AI systems?
4 How have you integrated automated API tests with CI/CD pipelines, and what metrics do you track to measure effectiveness?
5 What strategies do you use for testing the reliability of AI-driven systems in production environments?
Practice Interview Questions →

⚠️ Common Mistakes to Avoid

  • Applying with generic QA automation experience without highlighting specific AWS cloud testing or data pipeline validation
  • Failing to demonstrate hands-on experience with the specific tools mentioned (InfluxDB, Redshift, Grafana, Datadog, Pytest/TestNG)
  • Not showing how your work connects to reliability and monitoring of production systems, especially for AI-driven applications

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Hayden AI!

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