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.
Enterprise · Student career platform + new AI training data line
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 |
|---|---|---|
| Technical Lead Manager, Handshake AI Technical Lead Manager for Handshake AI, focusing on building and shipping production AI solutions. This player-coach role requires hands-on coding, system architecture, and team leadership, working with frontier AI labs on data, evals, and AI systems. | Ship | 8 |
| Staff Forward Deployed Engineer Staff Forward Deployed Engineer role at Handshake AI, focusing on defining and driving technical strategy for engineered solutions to strategic customers, including leading AI labs. The role involves architecting and delivering production-grade systems, setting technical direction, and influencing product and platform architecture. It requires deep customer engagement and scaling forward-deployed engineering as a function, with a strong emphasis on customer-facing AI products. | Ship | 7 |