Insurance · Insurance
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.
Currently tracking 5 active AI roles, down 36% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $103k–$175k (avg $138k).
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 |
| Lead Data Scientist Lead Data Scientist role focused on creating and deploying ML/AI solutions for marketing and business engagement within a regulated enterprise environment. Responsibilities include technical leadership, model development, platform integration, and team management, with a strong emphasis on production stability and compliance. | ShipPost-train | 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 |
| MLOps Engineer MLOps Engineer responsible for operationalizing AI/ML models, including LLM-based solutions, within the Azure ecosystem. This role involves designing, implementing, and maintaining end-to-end ML pipelines, managing infrastructure for model execution, and ensuring reproducibility, traceability, and observability. The engineer will also manage the operational lifecycle of generative models, including fine-tuning, evaluation, and RAG pipelines, while ensuring compliance with policies and standards. | ServePost-train | 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 |