Junior AI Engineer (Full Stack Engineering)
Junior AI Engineer (Full Stack Engineering)
MetLife- Posted 4 hours ago
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Job Description
Position: Junior AI Engineer (Full Stack Engineering)
Role Description
The Junior 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
Role Description
The Junior 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.
- Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent experience.
- At least 2 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.
- 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.
More Info
Key Skills
CI CD
Azure AI Foundry
API-first development
mobile frameworks
Copilot SDK
AI-assisted software delivery
Azure AppInsights
Elastic logging and monitoring
shift-left quality and security practices
GitHub Enterprise
Semantic Kernel
GitHub Copilot
LLM application patterns
RAG
AI agents
domain-driven design
