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GTM Engineering Intern

Unify
Posted 2 days ago, valid for 16 days
Location

San Francisco, CA, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Unify is seeking a candidate to join their GTM team to enhance systems that drive growth through technical execution and data analysis.
  • The role involves building internal tools, working with APIs, and developing systems for identifying buying signals.
  • Candidates should have at least 3 years of experience in a related field and a passion for AI and innovative product development.
  • The position offers a competitive salary of $85,000 to $100,000 per year, depending on experience.
  • Unify values curiosity, ambition, and craftsmanship in a fast-paced environment.

Unify is building the first AI-native outbound platform where agents and sellers work side by side. We help revenue teams identify buyers already in market, enrich accounts with data from 40+ sources, and execute personalized, multi-channel outreach—all from a single AI-powered workspace.

Trusted by some of the most innovative go-to-market teams, Unify enables reps to spend less time on manual work and more time building relationships, delivering up to 90% time savings on list building and 19% higher output per rep.

We're building a team of curious, ambitious people who care deeply about craftsmanship, move with urgency, and thrive in fast-paced environments. If you're excited about shaping the future of AI and building products that redefine how modern revenue teams work, we'd love to meet you.

About the role
Work with Unify's GTM team to build and improve the systems that power our growth motion. You’ll combine technical execution, data analysis, and experimentation to identify opportunities and turn them into scalable GTM workflows.

What you'll do

  • Build internal tools and automations for GTM workflows

  • Work with APIs, data sources, and AI models to enrich and analyze account and prospect data

  • Develop systems for identifying, scoring, and acting on buying signals

  • Run growth experiments and measure their impact

  • Improve the data infrastructure and workflows used by sales and growth teams

  • Ship projects end-to-end and iterate based on results




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