Full Stack Engineer

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Overview

The full stack software engineer designs, develops, and maintains software systems powering Yale School of Medicine's digital communications platforms, including a custom content management system (Beatrix) that serves hundreds of websites and a unified public web experience e.edu. The role spans both sides of the stack: building and refining React-based front-end interfaces-page templates, component libraries, interactive features-and developing the C#/.NET Core back-end services, APIs, and data layers that power them.

This is a mid-level engineering role on a small, high-impact Yale-based team that is actively transitioning to an AI-first development model-one where AI agents handle implementation, testing, and deployment, and engineers focus on architecture, orchestration, and quality.

The ideal candidate brings demonstrated experience using AI tools and agents to write, test, and ship production code-not as an experiment, but as a core part of how they work. They are equally comfortable building polished, accessible user interfaces as they are working in back-end services and database layers. They collaborate directly with product managers and designers, translate Figma designs into production-ready components, and contribute to the architectural decisions that shape platform direction.

This is not a position for someone who wants to write code the traditional way and occasionally use AI as a convenience tool. The team is moving toward a model where AI agents handle the majority of implementation, testing, and deployment. The engineer in this role is expected to embrace that shift fully-to be someone who has already made it, and who can help accelerate the rest of the team's transition.

This engineer will spend the majority of their time building and shipping features across both the front end and back end of Beatrix, YSM's custom content management system, and the public web experience e.edu. Day to day, this means writing React components and page templates that implement a cohesive design system; developing and maintaining C#/.NET Core APIs and MSSQL data layers;

and using AI coding tools as the primary method of development, not as an occasional assist.

The team is in the early stages of rebuilding Beatrix on a metadata-driven, AI-native architecture. This engineer will contribute directly to that effort-helping define how AI agents generate, test, and deploy code across the platform. They will also help codify infrastructure, improve deployment pipelines, and establish review patterns for AI-generated output. The role requires someone who can move fluidly between front-end and back-end work, operate with a high degree of autonomy, and bring forward new ideas about how the team works.

Key Responsibilities include:

* AI-first development. Use AI coding tools and agents (e.g., Claude Code, Augment, Cursor) as the primary method of writing, testing, and iterating on code. Contribute to defining and improving the team's AI-assisted development workflows.

* Front-end engineering. Build and maintain React-based user interfaces for both the public-facing website (medicine.yale.edu) and the Beatrix CMS authoring experience. Develop reusable component libraries, implement page-level templates from a cohesive design system, and ensure interfaces are responsive, accessible, and performant. Translate Figma designs into production-ready code.

* Back-end engineering. Develop and maintain C#/.NET Core APIs, MSSQL and No

SQL data layers, and the service architecture that powers Beatrix and related platforms. Work across the full data lifecycle from ingestion and transformation to API delivery.

* Platform architecture. Contribute to the design and build-out of Beatrix v2, a metadata-driven platform using a stable core engine and Lua scripting for domain behavior. In this architecture, the React front end is where the bulk of the engineering effort lives-interpreting metadata and Lua-defined logic into the interfaces users interact with. Help define patterns that allow AI to reliably generate, test, and deploy both front-end components and back-end features.

* AI orchestration and agent management. Configure, supervise, and improve AI agents that handle feature scaffolding, bug resolution, automated testing, and deployment. Treat this as a core engineering discipline, not an add-on.

* Infrastructure as code. Help codify and automate pipelines, deployments, monitoring, and environment management using tools like Terraform and Bicep so that infrastructure is documented, testable, and not dependent on institutional knowledge held by any one person or team.

* Code quality and review.…