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 43% 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 |
|---|---|---|
| Strategic Projects Lead, Coding This role involves leading coding data initiatives for AI and platform teams, coordinating SWE Fellows, designing and owning technical evaluation and annotation workflows, and ensuring delivery, margins, quality, and customer relationships. Responsibilities include writing and validating coding assessments, building rubric-driven code review processes, instrumenting quality signals, and adapting workflows. The role requires strong technical and analytical skills, coding proficiency, and stakeholder management. | Data | 7 |
| Manager, Strategic Projects Manager, Strategic Projects leading a team focused on AI data and evaluation work. Responsibilities include managing SPLs, driving project delivery (data pipelines, labeling workflows), translating needs into plans, owning performance metrics, ensuring a good experience for fellows, and partnering with Product/Engineering on tooling. Success involves consistent delivery, improved operational metrics, and strong team leadership. Requires 5+ years in operations, 2+ years managing teams, and experience with complex projects, ideally in AI data operations or ML ops. |
| DataEval Gate |
| 7 |