Lead Backend Engineer

We are looking for a Lead Backend Engineer with strong leadership capabilities and hands-on software development experience. This role is ideal for an engineer who can provide technical direction while remaining actively involved in architecture, coding, testing, deployment, and production support.

The team is responsible for building and modernizing student-facing products, including new applications and the transformation of legacy Java applications into modern AWS-based React/Node.js applications.

Engineers work in a poly-skilled environment, contributing not only to application development but also to automation, testing frameworks, operational readiness, and continuous improvement. Technical Skills

Candidates should be highly comfortable with the following technologies:

• AWS DynamoDB
• AWS Lambda
• AWS S3
• AWS SNS/SQS
• AWS EventBridge
• AWS Kinesis
• JavaScript (ES6)
• Node.js Development strong coding experience required
• OpenSearch / Elasticsearch
• React.js
• LLMs / Generative AI

About the Team

The team builds and maintains a broad range of student-focused products designed to help students with college, scholarship, career exploration, and planning.

The team works in an agile and collaborative environment that values creativity, curiosity, problem-solving, clean engineering practices, and scalable solutions.

Engineers are expected to contribute beyond coding by mentoring teammates, documenting solutions, collaborating with product and design teams, identifying risks early, and helping reduce technical debt. About the Opportunity

As a Lead Engineer, you will help shape the technical direction of the platform while delivering reliable and scalable applications.

You will work closely with product owners, architects, designers, and other engineers to translate business requirements into effective technical solutions. You will also have opportunities to explore emerging technologies, including Generative AI, and help establish engineering practices around their safe and effective implementation.

The role requires someone who is comfortable taking ownership of the complete development lifecycle, including:

• Requirements definition and analysis
• Application architecture and design
• Prototyping
• Coding
• Code reviews
• Testing
• Deployment
• Production support
• Documentation

Key Responsibilities Design & Development 60%

• Design and deliver high-quality software that is scalable, secure, reusable, and cloud-native.
• Leverage modern technologies and proven design patterns to build student-facing applications.
• Collaborate with product owners, architects, and stakeholders to maintain high engineering standards.
• Translate product ideas into actionable and verifiable technical changes.
• Design and implement solutions that allow rapid testing of innovative concepts, including React-based web applications.
• Create clear technical and non-technical documentation.
• Build prototypes strategically, focusing engineering effort on the most important functionality.
• Maintain clean, maintainable code and strong engineering standards.
• Ensure prototypes and solutions are structured for continued development and scalability.
• Continuously develop technical skills and stay current with rapidly evolving technologies.

Team Operations & Success 30%

• Participate in or lead Agile/Scrum ceremonies, including Sprint Planning, Backlog Grooming, Daily Scrum, and Demos.
• Provide thoughtful code reviews and mentor fellow engineers.
• Help the team solve complex technical challenges.
• Assist with production issue resolution and ensure reliable user experiences.
• Follow development standards, security practices, and CI/CD principles.
• Contribute effectively in a poly-skilled engineering environment.
• Serve as a technical Subject Matter Expert for implementing Generative AI applications.
• Work with Enterprise Architecture teams to review and establish implementation patterns involving Generative AI tools.
• Advise on and, where feasible, create tools and infrastructure that enable teams to safely deploy Generative AI solutions.

The ideal candidate is a hands-on technical leader who can:

• Lead architecture and technical decision-making.
• Develop production-quality backend applications.