Application Guide

How to Apply for Generative AI Engineer

at Archer

🏢 About Archer

Archer is pioneering sustainable urban air mobility with its electric vertical takeoff and landing (eVTOL) aircraft, aiming to reduce urban congestion and carbon emissions. Working here means contributing to cutting-edge transportation technology that could revolutionize how people commute in cities. The company's mission-driven focus on climate-friendly solutions creates a unique environment where engineering directly impacts environmental sustainability.

About This Role

This Generative AI Engineer role involves building LLM-powered applications that enhance natural language understanding and intelligent automation for Archer's aviation systems. You'll be responsible for developing RAG pipelines and agent-based workflows that support critical functions like conversational search and structured task execution. Your work will directly integrate AI capabilities into scalable backend systems that power next-generation urban transport solutions.

💡 A Day in the Life

A typical day might involve designing retrieval logic for aviation knowledge bases, optimizing embedding strategies for maintenance documentation, and implementing agent workflows for automated passenger support systems. You'd collaborate with aviation engineers to integrate AI capabilities into flight operations tools while ensuring systems meet rigorous reliability standards. Much of your time would be spent on continuous improvement of RAG pipelines and scaling backend systems that support real-time decision-making for urban air mobility operations.

🚀 Application Tools

Generate Cover Letter

AI-powered, tailored for Archer

Interview Prep

Practice questions for this role

🎯 Who Archer Is Looking For

  • Has 7-8 years of full-stack engineering experience specifically with cloud-native applications that have scaled to handle aviation or transportation-level demands
  • Possesses 2-4+ years of hands-on experience deploying Generative AI applications, with demonstrated expertise in RAG architecture optimization and retrieval workflow design
  • Has practical experience with multiple LLM ecosystems (OpenAI GPT, Azure OpenAI, AWS Bedrock, Gemini, or Vertex AI) and can articulate trade-offs between them
  • Can showcase experience designing agent-based workflows for reasoning and tool usage in production environments, ideally in safety-critical or regulated industries

📝 Tips for Applying to Archer

1

Highlight specific RAG pipeline projects where you optimized embeddings, chunking strategies, or retrieval logic - quantify improvements in latency or accuracy

2

Demonstrate how your full-stack experience enables you to build scalable backend systems that incorporate AI, not just prototype AI models

3

Showcase experience with agent-based workflows for structured task execution, particularly if related to automation or decision-making systems

4

Connect your AI experience to applications in regulated industries or systems requiring high reliability (like transportation, aviation, or safety-critical domains)

5

Tailor your examples to show how LLM-powered applications can support natural language understanding in complex technical domains like aviation systems

✉️ What to Emphasize in Your Cover Letter

['Explain how your RAG architecture experience can be applied to aviation documentation, maintenance procedures, or passenger interaction systems', 'Describe your approach to building scalable AI systems that maintain reliability in safety-conscious environments like urban air mobility', 'Connect your full-stack engineering background to creating production-ready AI applications, not just research prototypes', 'Express specific interest in how generative AI can enhance electric aviation operations, customer experiences, or operational efficiency']

Generate Cover Letter →

🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Study Archer's Midnight aircraft specifications and understand how AI could enhance its operational systems or passenger experience
  • → Research urban air mobility regulatory frameworks (FAA Part 135, etc.) and consider how AI applications must comply with aviation safety standards
  • → Explore Archer's sustainability mission and how AI could contribute to optimizing energy usage, route planning, or operational efficiency
  • → Review Archer's partnerships with United Airlines and other stakeholders to understand the ecosystem where these AI systems will operate

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk me through how you would design a RAG system for aircraft maintenance documentation retrieval and troubleshooting assistance
2 How would you implement agent-based workflows for automated flight scheduling or passenger query resolution using LLMs?
3 Describe your experience optimizing retrieval logic and ranking for time-sensitive or safety-critical information
4 How do you ensure the reliability and accuracy of LLM-powered applications in regulated transportation environments?
5 What metrics would you establish to evaluate and continuously improve conversational search systems for aviation operations?
Practice Interview Questions →

⚠️ Common Mistakes to Avoid

  • Focusing only on AI model development without demonstrating experience building production-ready, scalable backend systems
  • Presenting generic RAG examples without showing deep understanding of retrieval optimization, chunking strategies, or evaluation methodologies
  • Failing to connect AI experience to applications in regulated, safety-conscious, or transportation-related domains

📅 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 Archer!

← Back to Job Listing Apply Now →