• Contribute to the development of features and improvements across our platform using technologies like TypeScript, React, Golang, Python, and AWS • Collaborate with engineers, product managers, and designers to bring ideas to life • Participate in code reviews, team discussions, and design sessions to learn engineering best practices • Write clean, maintainable, and well-tested code with guidance from mentors • Debug issues, write tests, and help improve system reliability and performance • Learn how scalable systems are built, including exposure to: APIs and backend services, Frontend applications (web and mobile), Databases (PostgreSQL, DynamoDB), Cloud infrastructure (AWS, serverless/Lambda) • Contribute to one or more of our teams: Logistics / hub software, Consumer products (Returnista iOS app, Returns Portal), Merchant & location dashboards

• Lead architectural design and technical direction for PaaS features, services, and platform components, ensuring strategic and technical alignment. • Drive the development of complex software, producing high-quality, maintainable, and well-tested code across multiple technologies and platforms. • Provide technical leadership and mentorship to multiple engineering teams, fostering best practices in software development, code quality, and system architecture. • Collaborate closely with engineering managers, SRE, and stakeholders to gather requirements, translate them into technical specifications, and deliver innovative solutions. • Evaluate and implement new technologies, tools, and methodologies to enhance development processes and product capabilities. • Conduct thorough code reviews, offering constructive feedback and ensuring adherence to coding standards and architectural principles. • Troubleshoot and resolve complex technical issues, including root cause analysis and implementing preventative measures. • Serve as a subject matter expert in relevant technical domains, sharing knowledge and expertise across the organization. • Contribute to the continuous improvement of engineering processes, tools, and infrastructure.

• Choose appropriate architectural patterns (microservices, message queues, etc.). • Justify the choice of patterns in relation to the requirements. • Consider trade-offs between simplicity and flexibility. • Define clear strategies for handling increased load (scalability). • Implement failure recovery mechanisms (resilience). • Ensure the release control service remains available in case of failure of the daily consolidation. • Define how components communicate (protocols, message formats, etc.). • Choose appropriate integration tools and define their responsibilities. • Implement authentication, authorization and encryption (security). • Implement protection mechanisms against attacks (WAF, etc.). • Analyze the quality of decomposing the system into smaller, manageable parts. • Abstract and segregate responsibilities across layers. • Write readable, organized, and maintainable code. • Use the C# language efficiently. • Implement tests with good coverage, quality and relevance. • Meet mandatory technical requirements. • Fulfill business requirements. • Document the architecture clearly and concisely. • Create diagrams that represent the architecture. • Justify architectural decisions. • Define data flows. • Write clear and detailed instructions on how the application works and how to run it locally (Readme). • Centralize documentation. • Describe possible improvements or expansions to the system. • Demonstrate long-term vision and planning capability. • Discuss trade-offs and challenges faced during development.

• Review and refine AI-generated technical responses and code-based outputs in your engineering specialization. • Evaluate outputs for technical accuracy, sound engineering principles, and best practice adherence. • Draft realistic engineering scenarios, including architectural design, code review, troubleshooting, and scalability challenges. • Assess AI reasoning on complex engineering problems, software design patterns, system architecture, debugging, and optimization strategies. • Identify logical flaws, unrealistic assumptions, and gaps in technical approach. • Create scenario variations from the perspectives of different engineering stakeholders, such as tech lead, architect, or developer.