If you’re interested in this role, shoot Connor an email at connor@unifygtm.com. We look forward to hearing from you!

Location: San Francisco, New York City

Our mission is to build the first system-of-action for go-to-market teams, starting with an end to end platform powering warm outbound.

The status quo is that sellers spend the majority of their day doing administrative tasks. They’re confined to jotting notes, looking at LinkedIn profiles and monitoring Slack notifications. This needs to change.

Our team has been studying sales workflows for years, spotting the patterns and repetitive button clicks that hold sellers back. We’ve stood in their shoes, understood how to give them superpowers, and built products that unlocked their 7th gear.

Now we’re building with OpenAI models (they’re an investor) and several sales data vendors to change how go-to-market works. Today, outbound sales is dominated by cold, mass outreach that floods peoples inboxes and converts to deals at a tiny rate. We’re building a platform to power warm outbound, allowing go-to-market teams to get in touch with the right people at the exact time they’re looking for a solution.

Unify was founded January 17th, 2023 by Austin Hughes (former Ramp) and Connor Heggie (former Scale AI). Prior to Unify, Austin led Ramp’s growth product team focused on new customer acquisition, and Connor was a machine learning research engineer at Scale.

We’re a high energy team, well funded by Thrive, Emergence, OpenAI and 40+ business angels. Come join us in changing how go-to-market works.

As a senior software engineer, you will shape our platform architecture and design for the future of Unify. You will work closely with our founders to build out products zero to one, make foundational technical design decisions, and own large engineering scope. We’re using the latest in generative ML to supercharge sales, so you’ll be working on the cutting edge. This is a high impact, high visibility role where you will steer us towards scaling our products as we reach product market fit.