Premera Blue Cross
Insurance · Health insurance (Pacific NW)
Premera Blue Cross currently has six active job listings related to artificial intelligence. The majority of these roles, 50%, are focused on agents. The company is primarily hiring for Engineering positions. Common technical areas mentioned in their job descriptions include model serving, inference infrastructure, and RAG. In the last 30 days, Premera Blue Cross has posted two new AI roles.
Insurance · Health insurance (Pacific NW)
Currently tracking 5 active AI roles, with 13 new openings in the last 4 weeks. Primary focus: Ship · Engineering.
Premera Blue Cross currently has 6 active AI-related roles in our index. The most common open titles are: AI Engineer IV (3), Manager, Digital Claims Optimization, Site Reliability Engineer IV, Solution Architect/AI Engineer IV. Most positions are in Engineering.
Premera Blue Cross's active AI hiring is concentrated in: agents (50%), application (33%), serving infrastructure (17%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Premera Blue Cross is hiring AI talent in: United States (3 roles).
Job postings at Premera Blue Cross most frequently reference: model serving, inference infra, rag, llm observability, agent orchestration.
In the past 30 days, Premera Blue Cross has posted 2 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| AI Engineer III AI Engineer III at Premera Blue Cross, responsible for taking AI/ML solutions from concept to production implementation. This role involves designing, modeling, and coding AI-enabled solutions, collaborating cross-functionally, and building reliable AI infrastructure. Key responsibilities include developing AI systems using cloud resources, creating data pipelines, specifying low-latency APIs for model deployment, and maintaining production AI systems. | ServeAgent | 8 |
| Solution Architect/AI Engineer IV AI Engineer III role focused on taking AI/ML solutions from concept to production, involving system design, modeling, coding, and deployment of AI systems. Requires hands-on experience in developing and deploying ML algorithms and building reliable AI infrastructure, with a focus on productionizing models, creating data pipelines, and developing low-latency APIs for AI model integration. Experience with Azure AI services, prompt engineering, and ethical AI practices is preferred. | ServeAgent | 7 |