Application Guide
How to Apply for Founding Backend Engineer
at Mendria
🏢 About Mendria
Mendria is unique because it focuses on detecting and pricing financial risks that traditional models miss, working directly with major institutional investors like REITs and insurers. This presents an opportunity to build systems that directly impact high-stakes financial decisions in a specialized, data-driven niche.
About This Role
As a Founding Backend Engineer, you'll build the core infrastructure for data ingestion, model execution, and portfolio-scale processing that powers Mendria's risk intelligence platform. This role is impactful because you'll be creating the foundational systems that deliver underwriting insights to enterprise clients, directly enabling the company's mission.
💡 A Day in the Life
A typical day might involve designing and implementing data ingestion pipelines for new risk datasets, collaborating with modeling teams to ensure their computations run reliably at scale, and enhancing API endpoints that deliver underwriting intelligence to client dashboards. You'd also be implementing observability features and data quality checks while working on job orchestration systems to process portfolio-scale financial data.
🚀 Application Tools
🎯 Who Mendria Is Looking For
- A Python expert with production experience in FastAPI, Flask, or Django who can design clean APIs for financial data exposure
- Someone experienced with SQL databases and scalable data pipelines, specifically for financial or quantitative data processing
- A problem-solver who takes pride in building reliable systems with strong observability, data quality controls, and job orchestration
- A collaborative engineer comfortable working across engineering and modeling teams to ensure reproducible computation in cloud environments (AWS/GCP)
📝 Tips for Applying to Mendria
Highlight specific experience with financial data pipelines or quantitative systems, not just generic backend work
Demonstrate your understanding of data quality and observability in production systems with concrete examples
Show how you've worked across technical teams (like with data scientists or modelers) to ensure reproducible computation
Tailor your resume to emphasize Python backend frameworks (FastAPI/Flask/Django) and cloud infrastructure for data-intensive applications
Include metrics about system reliability or scalability you've achieved in previous roles, especially with financial or large datasets
✉️ What to Emphasize in Your Cover Letter
['Your experience with backend systems for data-intensive applications, particularly in financial or quantitative domains', 'Specific examples of building reliable APIs and data pipelines that served enterprise clients or dashboards', "How you've implemented data quality controls, job orchestration, or observability in previous roles", 'Your ability to collaborate across technical teams to ensure reproducible and predictable computation']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Research institutional investors, REITs, and the specific financial risks they face that traditional models might miss
- → Understand the landscape of financial risk modeling and where 'alternative data' or non-traditional approaches fit
- → Look into Mendria's potential clients (large REITs, insurers, family offices) and their technology needs
- → Explore current trends in underwriting intelligence and portfolio risk management technology
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Presenting only generic backend experience without financial data or quantitative system examples
- Focusing solely on coding skills without demonstrating system design for reliability and scalability
- Showing limited understanding of how backend systems support data science/modeling teams in production environments
📅 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:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!