Allstate
Insurance · Insurance
- HQ
- Northbrook, US
- Founded
- 1931
- Website
- allstate.com
Insurance · Insurance
Allstate currently has 12 active AI-related job listings. The majority of these roles, 67%, are focused on agents. Engineering is the dominant function, with 11 roles, and the majority of hiring is in the United States, with 9 positions. Frequent technology tags include agent orchestration, LLM observability, and model serving, suggesting a focus on managing and deploying AI agents. Over the last 30 days, Allstate has added 13 new AI roles, representing a 225% increase from the previous 30-day period.
Currently tracking 7 active AI roles, down 97% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $75k–$291k (avg $148k).
Allstate currently has 11 active AI-related roles in our index. The most common open titles are: AI Digital Product Manager, AI Engineer Lead, Data Scientist - Agentic AI (Hybrid), Director, Engineer (AI, Data & Security Tooling Ecosystem), Lead AI Cloud Platform Engineer. Most positions are in Engineering and Product.
Allstate's active AI hiring is concentrated in: agents (73%), serving infrastructure (18%), application (9%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Allstate is hiring AI talent in: United States (9 roles), United Kingdom (1 role).
Job postings at Allstate most frequently reference: agent orchestration, llm observability, model serving, rag, guardrails.
In the past 30 days, Allstate has posted 9 new AI-related roles. That is a +50% change versus the prior 30 days (6 → 9).
| Title | Stage | AI score |
|---|---|---|
| Data Engineer – Claims Data & AI Enablement Senior Consultant II Data Engineer supporting the design, development, and delivery of scalable data solutions for claims analytics, reporting, and AI-driven initiatives. The role focuses on making structured and unstructured data available for advanced analytics, reporting, and data science solutions, including emerging AI use cases. Responsibilities include developing data ingestion, transformation, and processing workflows, preparing curated datasets for ML and AI, integrating data from various sources, and applying DevOps practices. The role partners with data scientists and technology teams to support AI use cases and improve data platform needs. | Data | 5 |