MetLife
Insurance · Insurance
- HQ
- New York City, US
- Founded
- 1868
- Website
- metlife.com
Currently tracking 5 active AI roles, down 36% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $103k–$175k (avg $138k).
MetLife has six active job listings related to artificial intelligence. The majority of these roles, 50%, are focused on agents. The company is frequently seeking candidates with expertise in fine-tuning, RAG, and model serving. In the last 30 days, MetLife posted three new AI roles, a 40% decrease compared to the previous 30-day period.
Insurance · Insurance
MetLife currently has 9 active AI-related roles in our index. The most common open titles are: Data & AI Governance Lead, Enterprise AI Platform Operations Engineer, Lead Data Scientist, Lead Enterprise Architect – AI Solutions, MLOps Engineer. Most positions are in Engineering and Product.
MetLife's active AI hiring is concentrated in: agents (44%), application (22%), serving infrastructure (22%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Job postings at MetLife most frequently mention: Prompt Engineering, Machine Learning, Cloud Native, Azure, Agile / Scrum.
In the past 30 days, MetLife has posted 2 new AI-related roles. That is a -71% change versus the prior 30 days (7 → 2).
| Title | Stage | AI score |
|---|---|---|
| Principal Architect (AI, Cloud & Azure) Principal Architect role focused on defining and governing enterprise architectures for AI, Generative AI, and Agentic AI platforms, including model lifecycle management, orchestration, tooling, and integration. The role involves architecting LLM-based solutions using RAG, fine-tuning, prompt engineering, and agent patterns, and establishing standards for ML/GenAI tooling and MLOps/LLMOps pipelines. It also requires ensuring responsible AI principles and compliance, with a strong emphasis on Azure cloud architecture and infrastructure reliability. | AgentServe | 8 |
| Senior AI Scientist Senior AI Scientist at MetLife in Mexico City, focused on leading the development of advanced analytics, Machine Learning, and AI solutions to transform business problems into analytical capabilities. The role involves building end-to-end AI/ML solutions, developing statistical and ML models using Python and Azure, and translating business needs into technical solutions. Requires strong Python, SQL, and ML modeling skills, with knowledge of LLMs, Prompt Engineering, and Agile environments. | Agent | 7 |
| Lead Enterprise Architect – AI Solutions Lead Enterprise Architect for AI Solutions at MetLife, focusing on driving enterprise and solution architecture for AI/ML and Generative AI initiatives within the Retirement Income Solutions business. This role involves defining architectural roadmaps, guiding the adoption of modern cloud-native architectures, and establishing architecture standards. The architect will also mentor other architects and engineers, and has experience with AI/ML solutions, model integration, prompt engineering, AI governance, and agentic frameworks for enterprise automation. | AgentData | 7 |
| Data Scientist - Pet Insurance Data Scientist focused on designing, building, validating, and deploying production-grade rule-based and machine learning solutions to automate and augment claims adjudication. This role involves end-to-end ownership of AI capabilities, including feature engineering, training, deployment, monitoring, and developing LLM-enabled features for document understanding and workflow automation. Requires strong Python, SQL, Generative AI/LLM experience, and cloud MLOps skills. | AgentData | 7 |
| Sr Principal Enterprise Data Architect, AI Sr Principal Enterprise Data Architect responsible for shaping, governing, and advancing the enterprise data architecture strategy, with a strong focus on enabling analytics, AI, and emerging intelligent capabilities. This role guides the architectural design and validation of AI enabled solutions, including analytics accelerators, intelligent assistants, and data driven platforms, and supports the transition of successful pilots into production. | Agent | 7 |