How to apply for Staff Software Engineer, Backend

About Archer

Archer is at the forefront of urban air mobility, developing electric vertical takeoff and landing (eVTOL) aircraft to reduce urban congestion and carbon emissions. Working here means contributing to a breakthrough in transportation that is both sustainable and innovative, with a clear mission to make cities cleaner and more accessible.

About the role

As a Staff Software Engineer, Backend, you'll architect and build the core backend systems that handle real-time telemetry and event data from Archer's eVTOL aircraft. Your work on high-performance APIs and data pipelines directly supports critical functions like flight operations, safety monitoring, and AI-driven insights, making this role pivotal to the company's success.

A typical day

Your day might start with a stand-up to align with the data science team on new telemetry requirements, then you'll dive into designing a stream-processing job for real-time anomaly detection. After lunch, you could be optimizing a time-series database schema for faster queries, followed by a code review with frontend engineers to ensure API contracts are clean. The afternoon might involve debugging a latency spike in the data pipeline, collaborating with DevOps on deployment strategies, and ending with documenting your architecture decisions.

Who Archer is looking for

• You have 5+ years of backend engineering experience, with a strong focus on building real-time data pipelines and high-performance microservices.
• You are proficient in Java, Python, or Rust and have hands-on experience with stream-processing frameworks (e.g., Apache Kafka, Flink) and time-series databases.
• You have a deep understanding of data modeling for low-latency writes and fast queries, and you're comfortable with both relational and NoSQL databases.
• You thrive in cross-functional collaboration, working closely with frontend, AI, and data science teams to expose clean, structured data via scalable APIs.

Tips for this application

• Tailor your resume to highlight experience with real-time data processing, stream computing, and low-latency systems—keywords like Kafka, Flink, and time-series DBs are crucial.
• Include specific examples of how you've architected data models for high-frequency telemetry or IoT data, as this mirrors Archer's core needs.
• Mention any experience with aviation, aerospace, or safety-critical systems, even if tangential—it shows domain interest.
• In your cover letter, explicitly connect your backend expertise to Archer's mission of making urban air mobility safe and efficient.
• Prepare a concise portfolio or GitHub repo showcasing a project involving real-time data pipelines or high-performance APIs, and reference it in your application.

What to cover in your cover letter

["Emphasize your passion for sustainable aviation and how your backend skills directly enable Archer's aircraft operations.", 'Highlight specific projects where you built high-throughput data pipelines and stateful stream-processing applications.', 'Show your ability to collaborate across teams (frontend, data science) to deliver integrated solutions.', 'Demonstrate your experience with Java/Python/Rust and your comfort with performance optimization for real-time systems.']

Research before applying

• Read about Archer's eVTOL aircraft technology and their current milestones (e.g., Maker aircraft, FAA certification progress).
• Understand Archer's key competitors (Joby, Lilium) and how Archer differentiates itself in the urban air mobility market.
• Familiarize yourself with the regulatory landscape for eVTOL aircraft, especially FAA certification and safety standards.
• Review Archer's recent partnerships and manufacturing plans to gauge company growth and technical challenges.

Likely interview topics

Based on the job description, expect questions about:

• Design a real-time telemetry pipeline for eVTOL aircraft: how would you handle high-frequency data ingestion, processing, and storage?
• Explain your approach to data modeling for a time-series database to support low-latency writes and fast queries.
• How would you implement a stateful stream-processing application for cleaning and transforming sensor data?
• Describe a time you optimized a backend system for performance and reliability—what trade-offs did you consider?
• How would you expose AI model insights via scalable APIs, and what architectural patterns would you use?

Common mistakes to avoid

• Don't focus solely on web development or CRUD APIs—this role is about real-time, high-throughput data systems, not standard web backends.
• Avoid generic statements about 'passion for technology' without connecting it to Archer's specific mission or technical challenges.
• Don't overlook the importance of data modeling and schema design; emphasize your experience with time-series and caching layers.