Description and Requirements



Role Description



The AI Engineer (Full Stack Engineering) designs, develops, tests, deploys, and maintains modern cloud-native applications using an AI-first engineering model. The role requires strong full-stack capability, upfront architecture and specification skills, responsible use of AI coding assistants, and ownership of quality, security, reliability, and production readiness.



Key Responsibilities

• Apply AI-first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement.


• Translate business outcomes into clear technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria.


• Build secure, scalable, resilient, observable, and maintainable full-stack solutions.


• Use AI responsibly to improve engineering productivity and software delivery quality.


• Partner with product, architecture, security, operations, and business teams to deliver aligned outcomes.


• Support incident resolution, automation, simplification, and continuous improvement activities.

Candidate Qualifications

• Bachelor's degree in Computer Science , Engineering, Information Technology, or equivalent experience.


• At least 3 years of experience developing enterprise applications using modern full-stack, API, data, and cloud technologies.


• Hands-on experience with AI-assisted software delivery, GitHub Enterprise, and GitHub Copilot.


• Exposure to Azure AI Foundry, Copilot SDK, Semantic Kernel, AI agents, RAG, and LLM application patterns preferred.


• Strong knowledge of Agile, DevOps, CI/CD, automated testing, API-first development, domain-driven design, and shift-left quality and security practices.


• Ability to clearly articulate requirements, design intent, constraints, trade-offs, and outcomes for people and AI-assisted platforms.

Tech Stack

• AI & Developer Productivity: GitHub Enterprise, GitHub Copilot, Azure AI Foundry, Microsoft Copilot ecosystem, Copilot SDK, Semantic Kernel, AI agents, RAG, LLM patterns.


• Cloud & Architecture: Microsoft Azure, cloud-native architecture, microservices, APIs, containers/Kubernetes, event-driven architecture, observability.


• Delivery & Engineering: Azure DevOps, Git, CI/CD, automated testing, SonarQube, secure coding, infrastructure as code, Agile, DDD, API-first, ADRs, NFRs.


• Development & Operations: Java, Spring Boot, ReactJS, HTML, JavaScript, mobile frameworks, SQL/NoSQL, authentication/authorization, API management, Veracode, Azure AppInsights, Elastic, logging and monitoring.

About MetLife



Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World's 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East.



As part of our New Frontier strategy, MetLife is building an AI-enabled, people-centered future. We're looking for people who bring curiosity, adaptability, and a growth mindset as we use AI to enhance how we serve customers, support communities, and evolve the way work gets done. At MetLife, AI is a responsible partner that supports human judgment, creativity, and continuous improvement while helping us build trust, inclusion, and long-term value.



Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us!