Handshake
Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.
In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.
Why join Handshake now:
Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
Build a massive, fast-growing business with billions in revenue
Our go-to-market team wins on three things: being with the right customers, at the right moment, and bringing the right data and story to the conversation. Most of the work that keeps them from it — assembling account context, chasing signals across systems, running the recurring mechanics of the business — is work AI can now do. It isn't being done today because our collective intelligence is fragmented: account context, market signal, product usage signal, and operating knowledge live scattered across systems and people, where AI cannot reach it.
GTM Engineering is the build discipline that closes that gap. We centralize the intelligence and build the engines that run on it, so reps spend less time assembling context and doing tedious work, and more time with customers, with a sharper case in hand when they get there. The bet is if we centralize that intelligence and build reusable engines on top of it, we inflect growth. Every time we ship, it is a power-up to the whole GTM team — new business and customer, at once.
As a GTM Engineer, you’ll sit at the intersection of business systems, data, and AI, building workflows that help Sales, Account Management, Customer Success, and RevOps move faster and operate more intelligently. You’ll own the execution of AI-driven automation across our GTM stack, using tools like Salesforce, Gainsight, Gong, Nooks, Clay, and BigQuery.This is the technical seat on the team, a senior individual contributor who treats GTM as a software problem and ships software that does the work a rep used to do. You will inherit a live portfolio of automations, own the technical end of the build, and shape a team that is being built.
Mine the prospect base for signals and feed the pipeline: Be our Clay power user. Build enrichment waterfalls and signal-detection workflows (job changes, hiring, funding, tech-stack, and product-usage triggers) that continuously mine our prospect and account base, then score, prioritize, and route the highest-fit qualified leads straight to our account executives.
Build AI-powered workflows and agents: Design, build, and maintain AI-driven workflows and agents using a mix of workflow tools (Salesforce Flows, Workato) and code (e.g., Python, SQL).
Turn fuzzy problems into shipped systems: Translate ambiguous business problems and high-effort manual workflows into reliable AI-powered automation,
Ship reliable, maintainable systems: Own your builds end-to-end. Develop the technical documentation, monitoring, and testing frameworks that keep GTM systems and AI workflows reliable, observable, and easy to adopt.
Champion AI across GTM: Spread AI best practices across the go-to-market teams, pitch plays unprompted, and help the whole org operate more intelligently.
You're a Senior IC and an opinionated builder who thinks in systems and in outcomes. You tinker until an unfamiliar tool works, and you solve problems analytically across functions to get there.
3–5 years in GTM Engineering, RevOps, Marketing Ops, Sales Systems Engineering, or Growth Engineering, building software-grade automation for a B2B SaaS GTM organization
AI coding assistant fluency (Claude Code, Codex, or Cursor): you use one daily to scaffold, debug, and ship a working automation the same day you started it
Advanced Clay (or an equivalent enrichment + orchestration platform): you know when to reach for Clay and when to build something custom in Claude Code
SQL fluency: you can write and understand complex, multi-table queries, and you're comfortable in a warehouse layer (dbt, BigQuery)
Hands-on experience inside Salesforce (data model, Flows, formula fields — Apex is a plus): you understand how leads and accounts actually move through the system, and why data quality degrades over time
Ownership Mindset: you define scope with minimal direction and ship a good v1 in weeks over a perfect one that never ships.
5+ years total experience
Production experience with LLM APIs (Claude, OpenAI): prompt design, eval loops, error handling, and the difference between a demo and something you’d trust in production
Agent tooling and Model Context Protocol (MCP) experience (Claude Agent SDK, MCP servers, a shared library of skills/prompts/plugins)
Project experience in AI/ML, advanced analytics
Background in early careers or marketplace SaaS
Handshake delivers benefits that help you feel supported—and thrive at work and in life.
The below benefits are for full-time US employees.
🎯 Ownership: Equity in a fast-growing company
💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching
🍼 Family Support: Paid parental leave, fertility benefits, parental coaching
💝 Wellbeing: Medical, dental, and vision, mental health support, wellness stipend
📚 Growth: Learning stipend, ongoing development
💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office
🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days
🤝 Connection: Team outings & referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
Company size reports differ between sources.
Company data includes TheirStack, LinkedIn observations · last observed Sep 28, 2026.
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