Software Engineer II - Excel Team

Design, implement, test, ship, and operate AI-powered spreadsheet features; contribute to architecture, design, code reviews, debugging, deployment, monitoring, and operational readiness; and maintain high standards for code quality, maintainability, performance, reliability, security, and customer experience. Contribute to end-to-end AI product experiences spanning rich user interfaces, workbook and enterprise context, application logic, model orchestration, services, data access, and platform capabilities. Develop intelligent workflows that use large language models to understand user intent, reason over spreadsheet data, invoke appropriate tools, and help users calculate, analyze, visualize, organize, and share information. Build reliable, grounded agentic experiences that use workbook and permission-aware context, validated model outputs, evaluation, telemetry, and safeguards to complete multi-step tasks accurately and safely. Apply responsible AI practices through transparency, user control, privacy, security, guardrails, appropriate uncertainty, and fallbacks for incomplete or unsafe model output. Thrive in a fast-paced environment by rapidly prototyping with emerging models and tools, validating assumptions through evidence, incorporating learnings, and maturing successful concepts into robust production solutions. Collaborate across Engineering, Product Management, Design, Applied Science, Research, and partner teams to help define AI opportunities and deliver well-scoped spreadsheet features. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Experience designing, building, testing, deploying, and operating production software. Experience with full-stack, web, client, or distributed systems development and grounding in data structures, algorithms, software design, debugging, testing, and performance analysis. Hands-on experience developing with large language models, generative AI, machine learning, or natural-language interfaces through professional work, academic projects, or substantial personal projects is a plus. Ability to collaborate across disciplines, communicate technical trade-offs, learn about evolving AI technologies, and deliver results in ambiguous and rapidly changing problem spaces. Experience building high-quality production AI applications with AI development frameworks and orchestration systems, including agent orchestration, tool or function calling, retrieval and grounding, prompt and context engineering, structured outputs, evaluation, observability, and safeguards. Demonstrated ability to use AI-assisted development tools effectively and efficiently to accelerate implementation, debugging, testing, and documentation while maintaining rigorous engineering judgment, review, and validation. Experience developing rich, data-intensive applications using JavaScript or TypeScript, and a modern user-interface framework. Experience building spreadsheets, productivity, collaboration, analytics, data visualization, or business intelligence features.