Application Guide

How to Apply for Member of Technical Staff (Backend & Infrastructure)

at Jua

🏢 About Jua

Jua is revolutionizing climate prediction by developing AI-driven, high-accuracy weather forecasting models aimed at creating a sustainable future. Unlike traditional weather services, Jua combines cutting-edge AI with practical infrastructure to deliver actionable insights for real-world decision-making. Working here means contributing directly to climate resilience through innovative technology in Zürich's vibrant tech scene.

About This Role

As a Member of Technical Staff (Backend & Infrastructure), you'll design, develop, and deploy scalable backend pipelines and cloud infrastructure that power Jua's AI weather models. You'll play a key role in defining technical strategy, working closely with ML engineers to ensure models are performant and reliable for real-world applications. This role balances rapid iteration with long-term system stability, directly impacting how accurate weather predictions are delivered globally.

💡 A Day in the Life

A typical day involves collaborating with ML engineers to optimize backend pipelines for weather model deployment, using cloud infrastructure to ensure scalability and reliability. You might refactor critical systems to address performance bottlenecks, design new services for data processing, and participate in technical strategy discussions to balance rapid iteration with long-term stability. The role blends hands-on coding with architectural planning to support Jua's mission of delivering high-accuracy forecasts.

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🎯 Who Jua Is Looking For

  • Has 3+ years of experience deploying and supporting large-scale production systems, preferably in data-intensive or AI/ML environments
  • Demonstrates ability to make pragmatic architectural decisions that balance speed, scalability, and technical debt management
  • Possesses strong backend development skills with experience in cloud infrastructure (AWS, GCP, or Azure) and pipeline orchestration
  • Shows interest in climate tech and AI-driven applications, with experience collaborating with ML teams on model deployment

📝 Tips for Applying to Jua

1

Highlight specific examples of deploying large-scale production systems, quantifying impact (e.g., 'reduced latency by 30%' or 'scaled to handle 1M+ requests/day')

2

Emphasize experience with backend pipelines for AI/ML models, mentioning tools like Kubernetes, Docker, or cloud-native services relevant to Jua's tech stack

3

Tailor your resume to show how you've balanced rapid iteration with long-term stability, using concrete examples of refactoring or managing technical debt

4

Research Jua's public work (e.g., blog posts, GitHub) and mention how your skills align with their focus on AI-driven weather forecasting

5

Include a link to your GitHub or portfolio showcasing backend/infrastructure projects, especially if related to data processing or scalability

✉️ What to Emphasize in Your Cover Letter

["Explain why you're passionate about Jua's mission to revolutionize climate prediction with AI, linking it to your career goals", 'Provide a specific example of a backend or infrastructure project you led that improved speed, scalability, or reliability in a production environment', "Describe how you've collaborated with ML or data science teams to deploy models, ensuring performance and usability", 'Mention your approach to making pragmatic architectural decisions while managing technical debt, with a brief case study']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Explore Jua's website and blog for insights into their AI-driven weather forecasting models and technical challenges
  • → Look into the company's tech stack or public mentions (e.g., on LinkedIn or tech forums) to understand their infrastructure preferences
  • → Research Zürich's tech ecosystem and how Jua fits into the climate tech or AI startup scene in Switzerland
  • → Review Jua's mission and recent news to discuss how your work could contribute to sustainable climate prediction

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Discuss your experience designing and deploying backend pipelines for large-scale, data-intensive applications (e.g., weather data processing)
2 Explain how you've addressed performance bottlenecks or refactored critical systems in past roles, with measurable outcomes
3 Describe your approach to working with ML engineers to deploy models, including challenges around reliability and scalability
4 Share examples of making fast-paced architectural decisions that balanced rapid iteration with long-term stability
5 Talk about your experience with cloud infrastructure (e.g., AWS, GCP) and tools for orchestration, monitoring, and deployment in production
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⚠️ Common Mistakes to Avoid

  • Applying with a generic resume that doesn't highlight experience with large-scale production systems or backend/infrastructure work
  • Failing to demonstrate knowledge of Jua's focus on AI-driven weather forecasting or climate tech in your application
  • Overemphasizing theoretical knowledge without concrete examples of deploying scalable systems or collaborating with ML teams

📅 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 Jua!

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