Senior Full Stack Engineer

Techstars is building an operating system that centralizes how we run accelerator programs, support founders, engage the network, and drive investment decisions. As a Senior Full Stack Engineer you'll own features end to end — from the data behind them to the React UI in front of them, from design to go-live. That includes the AI-native parts of the product: search that spans the network, retrieval over founder and portfolio data, and assistive workflows that put the right context in front of the right person.

You'll also lead the wind-down of our legacy founder tools, consolidating what matters into OS and retiring the rest cleanly.

This is a small, high-trust team. We move fast, ship real things, and expect everyone to be able to hold a thread all the way through.

What you will do

• Own features on Techstars OS end to end — design, build, test, and ship, from data ingestion and API layers through to the web app

• Build AI-native features into the product: semantic and federated search across the network, retrieval over portfolio and founder data, and assistive workflows that surface the right context at the right moment

• Lead the migration and shutdown of legacy founder tools — including Techstars Universe and our application management system — consolidating functionality into OS or retiring it cleanly

• Work across our Enterprise Data Platform and OS to build the pipelines that feed real-time features, search, and AI use cases

• Raise the floor on reliability and velocity: tests, code review, and CI/CD practices that hold up as the team grows — including how we fold AI coding tools into that loop

• Act as a technical resource for the team — unblock others, weigh in on architecture, and keep context moving across time zones

What you bring

• Strong TypeScript and Python, and the judgment to know when to reach for each

• Solid React experience — you can build clean, functional UIs without a dedicated frontend team carrying you

• Proficiency with relational databases: data modeling, migrations, and query performance under real load. We use PostgreSQL

• Experience building data pipelines end to end — ingestion, transformation, and delivery to downstream consumers. We use event streaming, but experience with any comparable system transfers

• Experience shipping LLM-backed features to production: retrieval, embeddings, and the evaluation loop that keeps quality honest. You understand the hard part is uncertainty, evidence, and recovery — not the API call

• Comfortable operating containerized services in a major cloud with infrastructure defined as code. We run on GCP and AWS