Application Guide

How to Apply for Senior Software Engineer

at AECOM

🏢 About AECOM

AECOM is a global infrastructure consulting firm focused on sustainable development, making it unique for engineers who want their work to have tangible environmental and societal impact. The company's commitment to 'building sustainable legacies' means you'd be contributing to projects that address climate change and community resilience, not just commercial software.

About This Role

This Senior Software Engineer role focuses on integrating AI capabilities into AECOM's SaaS platform through backend systems and APIs, with specific ownership of ML performance, monitoring, and security. You'll be building the infrastructure that enables AI-driven solutions for sustainable infrastructure projects, making this role impactful at the intersection of technology and environmental innovation.

💡 A Day in the Life

A typical day might involve designing and implementing backend APIs that expose ML model predictions to AECOM's SaaS platform, collaborating with ML engineers to optimize model performance and monitoring dashboards, and participating in architecture discussions about scaling cloud-native ML infrastructure. You'd regularly work with product teams to understand user needs for sustainable infrastructure solutions and translate them into technical requirements.

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Interview Prep

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🎯 Who AECOM Is Looking For

  • Has 5+ years of backend development experience with specific expertise in building scalable APIs for data-intensive applications
  • Demonstrates practical experience with ML operations (MLOps) including model deployment, monitoring, and performance optimization in production environments
  • Shows proven ability to collaborate effectively across ML engineering, data engineering, and product teams in agile environments
  • Has experience with cloud-native architecture decisions for ML infrastructure on platforms like AWS, Azure, or GCP

📝 Tips for Applying to AECOM

1

Highlight specific examples of backend systems you've built that integrated AI/ML capabilities, quantifying performance improvements or scalability achievements

2

Demonstrate your understanding of AECOM's sustainability mission by connecting your technical experience to environmental or infrastructure applications

3

Showcase experience with ML monitoring tools (like MLflow, Weights & Biases, or custom solutions) and how you've ensured model reliability in production

4

Emphasize cross-functional collaboration experiences, particularly with ML engineers and data engineers on end-to-end feature delivery

5

Include concrete examples of your contributions to architecture decisions for scalable systems, especially those involving cloud-native ML infrastructure

✉️ What to Emphasize in Your Cover Letter

['Your experience developing backend systems that successfully integrated AI capabilities into SaaS platforms', 'Specific examples of taking ownership of ML performance, monitoring, or security in previous roles', "How your technical skills align with AECOM's mission of building sustainable infrastructure through innovation", 'Demonstrated ability to collaborate effectively with ML engineers, data engineers, and product teams']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → AECOM's specific sustainability initiatives and projects (check their Sustainability Report and project case studies)
  • → The company's existing SaaS platforms and how they might integrate AI (look for press releases about digital transformation)
  • → AECOM's work in infrastructure sectors where AI could be applied (transportation, water, energy, environmental)
  • → The company's technology partnerships or acquisitions that might indicate their AI/ML direction

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk us through your experience designing and implementing APIs that integrate ML models into production systems
2 How have you approached ML performance monitoring and what metrics do you consider most important for production AI systems?
3 Describe a time you collaborated with ML engineers and data engineers to deliver an end-to-end feature - what challenges arose and how did you overcome them?
4 What architecture patterns would you recommend for building scalable, cloud-native ML infrastructure, and what trade-offs would you consider?
5 How do you see AI/ML technology contributing to sustainable infrastructure solutions, and what experience do you have in this domain?
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⚠️ Common Mistakes to Avoid

  • Presenting only generic backend development experience without specific examples of AI/ML integration
  • Failing to demonstrate understanding of ML operations beyond basic model training
  • Not showing how your work connects to AECOM's sustainability mission or infrastructure focus

📅 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 AECOM!

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