• Lead the architectural design and development of significant software components, systems, and features, ensuring they meet functional and non-functional requirements. • Define and drive the technical strategy and roadmap for key product areas or infrastructure components, aligning with broader company objectives. • Tackle the most complex technical challenges across multiple systems to deliver robust, well-engineered solutions. • Mentor and provide technical guidance to senior and junior engineers, fostering a culture of excellence, innovation, and continuous learning. • Collaborate with product managers, architects, and designers to define requirements and make key technical decisions. • Champion best practices for software development, including code quality, testing methodologies, CI/CD pipelines, and system observability. • Identify, analyze, and resolve complex technical issues and production incidents to improve system reliability and performance. • Stay current with emerging technologies and industry trends to advocate for their adoption where they provide significant value. • Uphold engineering standards and contribute to a culture of operational excellence. • Drive progress on complex projects with strong ownership from conception through deployment. • Participate in a 24/7 on-call rotation to provide timely resolution to production issues.

• Design and Build ML Models for generative tasks, such as text generation and image synthesis • Optimize Generative AI Models for performance enhancements • Prepare and manage datasets, handle augmentation, and create synthetic data • Train large-scale generative models; fine-tune pre-trained models for specific use cases • Evaluate the model’s performance using various metrics and iterate on design • Collaborate with cross-functional teams to integrate ML models into production systems • Conduct research experiments and build prototypes to test new algorithms • Deploy generative models into production environments ensuring scalability and reliability • Stay updated with trends in generative AI and machine learning

• Supports our product, sales, and consulting teams with building and maintaining scalable, web-based applications. • Design, develop, and maintain full-stack web applications that support Generative AI projects. • Work closely with AI researchers to integrate Generative AI models into applications, ensuring seamless functionality and optimal performance. • Monitor and optimize the performance of applications and AI integrations to ensure responsiveness and efficiency. • Coordinate with data scientists, engineers, AI researchers, and other developers to understand project requirements and deliver solutions that meet technical and business needs. • Identify and resolve issues related to application performance, AI model interactions, and data handling. • Apply best practices in coding, testing, and deployment to ensure high-quality software development and robust application performance. • Keep abreast of the latest developments in AI technologies, and software engineering practices.

• Design & Build Across the Stack – Design and implement features end-to-end, from robust backend services and APIs in Java/Kotlin and Spring Boot to polished, responsive user interfaces in Angular. Own the full lifecycle of features - database schema to UI component - while maintaining high code quality standards and contributing to architectural decisions. • Collaborate & Deliver – Work within agile product teams to deliver high-quality features, participate in code reviews, and contribute to technical discussions across both backend and frontend. Partner with designers and product managers to translate requirements into complete, working solutions. • Innovate & Improve – Tackle complex technical problems that span the full stack, propose innovative solutions and continuously improve our development practices, tooling, and user experience. • AI-Accelerated Development – Leverage AI coding assistants and tools to accelerate development velocity across the full stack. Help establish and refine AI-assisted development workflows, prompting strategies, and best practices for the team. Evaluate and adopt emerging AI tools that improve code quality, testing, and developer productivity. Contribute to a culture where AI is a natural part of the engineering workflow, not an afterthought.