• Architects and builds enterprise software applications on cloud platforms using AWS technologies. • Develops software in a fast-paced Agile development environment. • Builds microservices and Application Programming Interfaces (APIs) for high-scale, high-availability data pipelines dealing with sensitive customer financial data. • Maintains and secures data in multiple databases to ensure data integrity, availability and performance. • Contributes to the development of test automation. • Provides business solutions by developing complex or multiple software applications. • Develops software system testing and validation procedures, programming, and documentation. • Coordinates software system installation and monitors its functioning to ensure specifications are met. • Develops original and creative technical solutions to on-going development efforts. • Designs applications or subsystems on major projects and for/in multiple platforms. • Develops applications for multiple projects supporting several divisional initiatives. • Supports and performs all phases of testing leading to implementation. • Assists in the planning and conducting of user acceptance testing. • Develops comprehensive documentation for multiple applications supporting several corporate initiatives. • Responsible for post-installation testing of any problems. • Establishes project plans for projects of moderate scope. • Works on complex assignments and often multiple phases of a project. • Performs independent and complex technical and functional analysis for multiple projects supporting several initiatives.

• Implementing Observability Frameworks: Building the tools and templates that provide visibility into model performance, data drift, and training statistics, ensuring our continuous retraining loops are robust. • Engineering for Efficiency: Developing systems to track and optimize compute costs and training performance, allowing us to scale our ML efforts sustainably. • Building Experimentation Tooling: Executing on the roadmap for internal tools that enable Data Scientists and ML Engineers to iterate and deploy experiments with minimal friction. • Developing SaaS-grade ML Services: Writing high-quality, maintainable Python code to build and automate services that sit at the core of our ML lifecycle. • Bridge-Building: Working alongside our Staff Engineer to implement architectural designs and collaborating with SRE/DevXP teams to ensure our solutions are production-ready and easily managed.

• Exhibit mastery of the ‘In-Store’ team’s domain, taking a leading role in the design and architecture of complex systems and influencing technical direction and strategy. • Own the delivery of large-scale features and projects, coordinating efforts across multiple teams and ensuring alignment with overall business objectives. • Provide mentorship and technical leadership to both junior and senior engineers, helping to grow the technical expertise within the team and fostering a culture of continuous improvement. • Collaborate closely with Product, Design, and other stakeholders to shape requirements, making architectural and technical decisions that balance quality, performance, and delivery timelines. • Ensure the implementation of high-quality, resilient, and scalable distributed systems, incorporating resilience mechanisms and best practices. • Lead troubleshooting and incident management efforts, taking a proactive role in resolving critical production issues and improving system reliability. • Advocate for and implements improvements in development practices, such as enhancing CI/CD processes, optimising infrastructure as code, and increasing test automation coverage. • Coordinate and lead cross-team technical initiatives, ensuring consistency and integration between various services and platforms. • Stay ahead of emerging technologies and trends, assessing new tools and techniques to enhance the team's capabilities. • Demonstrate ownership of the team's delivery pipeline, ensuring that code quality, testing standards, and deployment practices are continuously optimised.

• Integrating state of the art learning science into our product to enable learners and teachers to quickly identify and address learning gaps on the fly. • Partnering with public school districts with a high percentage of Free and Reduced Price Lunch students to build and scale our teacher and learner tools to millions of learners who otherwise would not have discovered us. • Building tools for teachers to use Khan Academy as a strategic supplement in their classrooms. • Harnessing the power of AI to deliver the product capabilities where applicable • Collaborating with cross-functional teams to deliver high-quality software and solutions.