PitchBook
Fintech · Private market data & analytics
PitchBook currently has 10 active AI-related job listings. The majority of these roles, 70%, are focused on agents. Engineering is the dominant function with 7 roles, followed by Product with 3. The company is hiring for roles that involve model serving, LLM observability, and agent orchestration.
Fintech · Private market data & analytics
Currently tracking 3 active AI roles, up 107% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $140k–$175k (avg $158k).
PitchBook currently has 6 active AI-related roles in our index. The most common open titles are: Manager, Engineering, AI & ML, Principal Product Manager, Deal Sourcing, Product Manager, Technical Platform Engineering, Sr. Director of Engineering, Data Collections Technology, Sr. Machine Learning Engineer. Most positions are in Product and Engineering.
PitchBook's active AI hiring is concentrated in: agents (50%), application (17%), post-training (17%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
PitchBook is hiring AI talent in: United States (6 roles).
Job postings at PitchBook most frequently reference: llm observability, model serving, fine tuning, rag, vector db.
In the past 30 days, PitchBook has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Sr. Director of Engineering, Data Collections Technology Sr. Director of Engineering, Data Collections Technology at PitchBook. This role focuses on architecting, building, and operating the foundational platform collection engine for PitchBook's proprietary data. It involves defining and executing the technology strategy for data acquisition, processing, and integration, including scalable ingestion pipelines and data storage solutions. The role also involves coordinating with centralized AI/ML teams to leverage AI-driven extraction and enrichment models, and leading a global engineering team to ensure reliability, efficiency, and throughput of the data processing infrastructure. | Data | 5 |