Handshake currently has 68 active AI-related job listings. The majority of these roles, 60%, are focused on data, with a further 15% in agents. Research and Engineering are the most frequent functions hiring for these positions. Recent hiring activity shows a significant increase, with 23 new AI roles posted in the last 30 days, representing a 92% rise compared to the preceding 30-day period.
Currently tracking 23 active AI roles, down 48% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Handshake currently has 65 active AI-related roles in our index. The most common open titles are: Music Producer - AI Trainer (2), Strategic Projects Lead, Coding (2), 3D Slicer Specialist - AI Trainer , AI Red Teamer, LLM Generalist, Analog Engineer - AI Trainer. Most positions are in Engineering and Research.
Handshake's active AI hiring is concentrated in: data (66%), agents (15%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Handshake is hiring AI talent in: United States (22 roles), India (4 roles).
Job postings at Handshake most frequently reference: evals, synthetic data, model serving, agent orchestration, llm observability.
In the past 30 days, Handshake has posted 10 new AI-related roles. That is a -57% change versus the prior 30 days (23 → 10).
| Title | Stage | AI score |
|---|---|---|
| Senior Product Manager, RL Environments — Handshake AI Senior Product Manager to own the product surface that turns RL environment creation from a bespoke, weeks-long lift into a repeatable factory. This role will design and ship the platform that compresses lead time, replaces hand-built workflows with self-serve tooling, and lets a small team of operators turn out high-quality environments for any vertical. | DataEval Gate | 8 |
| Data Development, Principal This Principal Data Development role focuses on sourcing, negotiating, and closing data partnerships with companies and institutions to supply proprietary real-world data to frontier AI labs for training next-generation AI models. The role involves translating data requirements between AI labs and enterprise leaders, structuring commercial and compensation models, and managing senior stakeholder relationships. | Data | 7 |