• Designing and implementing large data, extremely high-volume, fault-tolerant, scalable backend systems that process and manage petabytes of customer data. • Working to improve algorithms built to schedule load on clusters of thousands of machines elastically at runtime. • Improving systems to provide performance guarantees to customers in a shared-everything multi-tenant architecture. • Contributing to the re-architecting of our internal message processing technology to petabyte per day scale. • Helping manage exabytes of data using the latest and greatest technologies such as Kafka, Kubernetes and Docker. • Partnering across Sumo interfacing with multiple teams including Search, Security and Metrics & Tracing to identify requirements and architect solutions to meet their data core ingest needs.

• Design, develop, and maintain backend services using Java, Spring Boot, and modern architectural patterns • Build intuitive, performant front-end experiences using React, Angular, or Vue • Lead technical design discussions and contribute to architectural decisions • Integrate AI/ML capabilities into applications (e.g., embeddings, LLM-powered features, intelligent automation) • Use AI-assisted development tools to accelerate coding, testing, documentation, and refactoring • Mentor junior engineers and promote engineering best practices across the team • Collaborate closely with product, data, and AI teams to deliver end-to-end solutions • Contribute to CI/CD pipelines, cloud deployments, observability, and performance optimization • Ensure security, scalability, and maintainability across the full stack

• Develop and maintain backend services using Java, Spring Boot, and related frameworks • Build responsive, user-friendly front-end features using modern JavaScript/TypeScript frameworks (e.g., React, Angular, or Vue) • Participate in design discussions, code reviews, and sprint ceremonies • Collaborate with cross-functional team members to deliver high-quality features end-to-end • Write clean, maintainable, and testable code following engineering best practices • Leverage AI-assisted tools to accelerate development and improve code quality • Troubleshoot, debug, and optimize applications for performance and reliability • Contribute to CI/CD pipelines, cloud deployments, and automation efforts

• Lead the technical design and architecture of full‑stack Java applications using Spring Boot and modern front‑end frameworks • Drive the integration of AI/ML capabilities into enterprise systems, including LLM‑powered features, intelligent automation, and AI‑assisted workflows • Provide hands‑on development while guiding the team in best practices, code quality, and modern engineering standards • Mentor and coach engineers across multiple levels, fostering growth and technical excellence • Collaborate closely with product, data, and AI teams to define technical strategy and deliver end‑to‑end solutions • Oversee system performance, scalability, observability, and security across the stack • Champion the use of AI‑assisted engineering tools to improve velocity, reliability, and developer experience • Facilitate technical discussions with clients, translating complex concepts into clear recommendations • Contribute to CI/CD pipelines, cloud architecture, and DevOps practices to ensure smooth, reliable deployments