Lead Full Stack Software Engineer

Job description

Description and Requirements Role Value Proposition MetLife is offering an exciting opportunity to contribute to our digital and AI transformation journey. We are moving to an AI-first way of working, where engineers, AI agents and copilots are core collaborators across the software delivery lifecycle. The engineers who thrive in this model are those who can think clearly upfront, specify intent and constraints explicitly, and direct AI systems with precision – while retaining full ownership, judgment, and accountability for what gets built.

Role Description The AI Engineer (Full Stack Engineering) is responsible for the design, development, and maintenance of cloud native/modern software solutions, increasingly built in partnership with AI coding agents and copilots. Success in this role depends as much on strong upfront architecture, design, and specification skills as it does on hands-on coding – and on the ability to clearly articulate intent, constraints, and acceptance criteria so that both AI systems and human collaborators can execute against them reliably.

Key Responsibilities

Apply AI-first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement. Create clear functional and technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria that guide high-quality delivery. Design, develop, test, deploy, and maintain modern full-stack, cloud-native applications that are secure, scalable, resilient, observable, and maintainable.

Use AI responsibly to accelerate engineering productivity while retaining accountability for code quality, design correctness, testing, security, and production readiness. Partner with product owners, architects, security, operations, and business stakeholders to translate business outcomes into executable engineering plans. Review solution designs, code, tests, and operational readiness to ensure consistency with enterprise architecture, security, compliance, and engineering standards.

Investigate and resolve production incidents, service requests, and performance issues while driving automation, simplification, and continuous improvement.

Candidate Qualifications

Education: Bachelor of Computer Science, Engineering, Information Technology, or equivalent experience.

Experience

Minimum 7 years of experience developing enterprise applications using modern full-stack, API, data, and cloud technology capabilities. Hands-on experience with AI-first engineering practices and AI-assisted software delivery in a modern engineering environment. Experience with GitHub Enterprise and GitHub Copilot; exposure to Microsoft AI capabilities such as Azure AI Foundry, Copilot SDK, Semantic Kernel, AI agents, RAG, and LLM-based application patterns is preferred.

Experience developing secure, mission-critical, cloud-native applications in complex or regulated enterprise environments. Proficiency in Agile, CI/CD, DevOps, automated testing, shift-left engineering, domain-driven design, API-first development, and modern architecture patterns.

Technical articulation

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

Collaboration

Proven ability to work effectively with global, multicultural, cross-functional teams.

Tech Stack AI-First Engineering & Developer Productivity

GitHub Enterprise, GitHub Copilot, Azure AI Foundry, Microsoft Copilot ecosystem, Copilot SDK, Semantic Kernel, AI agents, RAG, LLM application patterns Cloud & Modern Architecture: Microsoft Azure, cloud-native architecture, microservices, APIs, containers/Kubernetes, event-driven architecture, observability DevOps & Delivery: Azure DevOps, Git, CI/CD, automated testing, SonarQube, secure coding, infrastructure as code Engineering Practices: Agile, domain-driven design, API-first development, Architecture Decision Records (ADR’s) , N o - F unctional R equirement s ( NFR’s) , shift-left quality and security Development Frameworks and Languages: Java, Spring Boot, ReactJS, HTML, JavaScript, mobile frameworks, SQL/NoSQL databases Security, Integration & Monitoring: Authentication/authorization, API management, Veracode, Azure AppInsights, Elastic, enterprise logging and monitoring