Senior Software Engineer at Stanford University in Stanford, CA

Senior Software Engineer

Location: Stanford, CA, United States

Stanford's Graduate School of Business (GSB) has built a global reputation based on its immersive and innovative management programs. We provide students a transformative leadership experience, pushing the boundaries of knowledge with faculty research, and offering a portfolio of entrepreneurial and non-degree programs that deliver global impact. We invite you to be part of our mission of developing innovative, principled, and insightful leaders who change lives, change organizations, and change the world.

Success at the GSB is defined by The GSB Way - a commitment to shared purpose, community, and excellence in all that we do. We seek individuals who elevate themselves and those around them through the practice of academic candor, generous collaboration, and bringing curiosity and rigor to solving meaningful problems. At the GSB, impact means taking ownership and contributing to a purpose-driven, collaborative, and high-performing community in service to the institution’s mission.

The Digital Solutions department of the Stanford Graduate School of Business seeks a Senior Software Engineer who will work on several web applications and cloud platforms.

In this role, along with supporting operational activities, you will also have the opportunity to contribute towards all phases of a delivery project, including systems analysis, architecture and technical design, development, build & release, and maintenance. You will be expected to provide innovative technology solutions to grow and stabilize the technology platforms along with improving the processes. You are a self-motivated, rapid learner, a seasoned thought partner, and an exceptional communicator with the ability to translate between business and technical partners.

Primary responsibilities include:

• Design and develop complex applications, web solutions, and integrations that address business needs.
• Quickly assess new ideas for feasibility, value, data availability, security, cost, and operational needs. Build prototypes, validate assumptions with users, and recommend whether and how to proceed.
• Develop AI-enabled applications and workflows using appropriate models, APIs, retrieval techniques, and tools. Use AI development tools effectively while remaining accountable for code quality and correctness.
• Convert successful prototypes into secure, scalable production applications with automated testing, deployment pipelines, monitoring, and rollback capabilities.
• Incorporate security and privacy throughout development, including access controls, sensitive data protection, and safeguards against AI-specific risks.
• Own the application life cycle, including deployment, production support, documentation, maintenance, dependency and model upgrades, migration, and retirement.
• Oversee testing, debugging, and change control. Evaluate application and AI performance, reliability, output quality, latency, and cost, and address failures and regressions.
• Lead projects, troubleshoot complex problems, mentor engineers, establish standards, and contribute to long-term technical planning. Evaluate emerging technologies through hands-on experimentation and guide appropriate adoption.
• Collaborate with business users, analysts, QA, and distributed remote technical teams across time zones to improve processes and deliver value. Exemplify GSB principles of open, honest, and timely communication, personal ownership, and innovation.
• Perform other duties as assigned.

To be successful in this position, you will bring:

• Bachelor's degree in Computer Science, Software Engineering, or a related discipline and eight years of increasing responsibility in software development, or a combination of education and relevant experience.
• At least two years of sustained, hands-on experience building, evaluating, and improving AI-enabled applications or substantive AI workflows. Occasional use of chatbots, AI plugins, or code assistants alone does not meet this requirement.
• Demonstrable AI experience gained through professional work, applied research, open-source contributions, or sustained independent projects. Ability to explain your implementations, experiments, technical decisions, failures, and improvements. Examples may be anonymized; public repositories are not required.
• Proven ability to independently assess ambiguous ideas, rapidly build working prototypes, and deliver and support production applications, including AI-enabled solutions.
• Practical experience with model APIs or SDKs, prompt and context design, and relevant patterns such as retrieval-augmented generation, structured outputs, or tool calling. Ability to evaluate results, diagnose failures, and balance quality, latency, cost, and privacy.
• Experience using AI coding assistants or agentic development tools for substantive development, debugging, testing, or refactoring, with the ability to understand, validate, and maintain the resulting code.
• Strong coding skills in at least one language such as Java, Python, PHP, or C#, and experience with frontend and backend web development, including JavaScript frameworks such as React or NextJS.
• Demonstrated understanding of software architecture, testing, deployment, and life cycle management, including secure coding, scalability, accessibility, complex workflows, and system integration.
• Skills in one or more areas such as API development, service-oriented architecture, cloud computing, MVC, or mobile application development.
• Demonstrated technical leadership, mentoring, and continuous learning, with experience working in distributed agile/scrum teams and explaining technical tradeoffs to technical and nontechnical audiences.