Application Guide
How to Apply for Senior Software Engineer
at AECOM
🏢 About AECOM
AECOM is a global infrastructure consulting firm that uniquely combines engineering, design, and sustainability expertise to solve complex challenges. Working here means contributing to tangible projects that shape communities and the environment, from transportation systems to water resources, with a strong emphasis on innovation and positive legacy. Their focus on 'sustainable legacies' through infrastructure and environmental solutions offers engineers a chance to apply technical skills toward meaningful societal impact.
About This Role
This Senior Software Engineer role sits at the critical intersection of backend development and machine learning operations, specifically focused on turning AI research into reliable, scalable production tools within AECOM's SaaS platform. You'll own the performance, monitoring, and security of ML systems while collaborating cross-functionally to integrate AI capabilities that deliver real value to users in infrastructure and environmental domains. This position is impactful because it directly enables AECOM to leverage cutting-edge AI to enhance their sustainable infrastructure solutions.
💡 A Day in the Life
A typical day might start with reviewing ML model performance dashboards and alerts to ensure systems are running smoothly, then collaborating with ML engineers to troubleshoot any issues or optimize pipelines. You could spend time designing or coding backend APIs to integrate new AI features into the SaaS platform, followed by architecture discussions with the team on scaling cloud-native infrastructure. The day often ends with cross-functional meetings to align on product deliverables, ensuring AI tools meet user needs for sustainable infrastructure solutions.
🚀 Application Tools
🎯 Who AECOM Is Looking For
- Has 5+ years of backend software engineering experience with proven ability to design and develop robust APIs and systems that integrate complex components
- Possesses hands-on experience with ML operations (MLOps) tools and practices, such as model deployment, monitoring, versioning, and pipeline orchestration in production environments
- Demonstrates expertise in building and maintaining cloud-native, scalable architectures on platforms like AWS, Azure, or GCP, with an understanding of infrastructure-as-code and containerization
- Can show experience collaborating effectively with ML engineers, data engineers, and product teams to deliver end-to-end features, ideally in a SaaS or platform context
📝 Tips for Applying to AECOM
Tailor your resume to explicitly highlight experience with MLOps tools (e.g., MLflow, Kubeflow, Sagemaker) and cloud-native ML infrastructure, not just general backend or ML knowledge
Emphasize any projects or roles where you've operationalized AI/ML models in production, especially at scale, and quantify results related to performance, reliability, or efficiency gains
Research AECOM's current projects or tech initiatives (e.g., digital twins, AI for infrastructure) and mention how your skills align with their focus on sustainable, innovative solutions
Since the role is remote, showcase experience with remote collaboration tools and practices, and highlight any past success in distributed teams building SaaS platforms
Include a link to your GitHub or portfolio with relevant code samples, especially backend/API projects or ML infrastructure work, to demonstrate hands-on capability
✉️ What to Emphasize in Your Cover Letter
["Explain your specific experience with MLOps and how you've ensured AI models run reliably and efficiently in production, linking it to AECOM's goal of turning research into real-world tools", "Highlight your ability to own ML performance, monitoring, and security, and provide a brief example of how you've handled these responsibilities in past roles", "Connect your cloud-native architecture skills to scalable systems, emphasizing how you've contributed to infrastructure decisions that support growth and resilience", "Express genuine interest in AECOM's mission of building sustainable legacies through infrastructure and environmental solutions, and explain why you're motivated to apply software engineering to this domain"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore AECOM's recent projects and initiatives in digital innovation, such as their use of AI, IoT, or data analytics in infrastructure (check their website, news, or case studies)
- → Investigate their SaaS platform offerings or tech stack mentions to understand the context where you'll be integrating AI (look for terms like 'digital solutions' or 'platforms' in their materials)
- → Learn about their company values and sustainability commitments, like the 'Sustainable Legacies' strategy, to align your application with their mission-driven culture
- → Review any public information on their engineering or tech teams, such as blog posts or conference talks, to gauge their technical culture and priorities
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Submitting a generic resume that doesn't specifically address MLOps, cloud-native architecture, or backend/API development for AI integration, as these are core requirements
- Focusing solely on machine learning theory or research without demonstrating hands-on experience in operationalizing models in production environments
- Neglecting to show how your skills relate to AECOM's industry (infrastructure/environment) or mission, making your application seem disconnected from their context
📅 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!