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Forward Deployed Engineer, Enterprise AI

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Handshake
Full Time position
Listed on 2026-09-18
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 260000 USD Yearly USD 180000.00 260000.00 YEAR
Job Description & How to Apply Below

About 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

About Handshake AI

Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on

About the Role

As a Forward Deployed Engineer at Handshake AI Enterprise, you'll embed directly inside enterprise customer environments as part of a small, expert team. You'll learn each customer's business deeply — their workflows, their bottlenecks, where the real leverage is — and translate that understanding into production-grade AI agents that measurably change how they operate.

This isn't an implementation or consulting role. You'll own the full stack: defining the solution, building and deploying agents, designing evals, and iterating until performance actually moves. Over time, you'll become a genuine domain expert in your customer's vertical — and use that expertise to build AI that keeps getting better.

We're looking for engineers across a range of experience — from those who've already shipped real AI in production, to seasoned engineers ready to set the technical bar for the team. If you've built AI that works in the real world and want to do it again at much higher stakes — with better data, closer lab relationships, and a founding team that moves fast — this is the role.

  • Embed directly with enterprise customers as part of a small deployment team, developing deep understanding of their business and workflows

  • Define AI-driven solutions based on real business needs — not theoretical use cases

  • Build and deploy production-grade agents tailored to specific customer use cases, owning end-to-end delivery

  • Design and run evals to measure agent performance; iterate and hill-climb until results move

  • Become a domain expert in your customer's vertical and use that expertise to build better AI over time

  • Work closely with Product and Platform engineers on your team to ship cohesive, reliable solutions

  • Establish engineering best practices, agent patterns, and reusable frameworks that help the forward-deployed team scale output without sacrificing quality

  • Surface insights from deployments that inform Handshake's platform and product roadmap

Location:
San Francisco, CA | 5 days / week in-office

Desired Capabilities
  • Full-stack engineering experience with strong backend depth

  • Real-world experience building and shipping AI applications in production — not just fine-tuning or prototyping

  • Strong understanding of agent architectures, evals, and how to measure and systematically improve AI performance

  • Comfort working directly with enterprise…

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