AI Engineer

MetLife; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

MetLife is seeking an AI Engineer (Full Stack) to design, build, test, deploy, and maintain cloud-native applications using an AI-first approach. You will own quality, security, and production readiness while collaborating across product, architecture, security, and operations teams.

The role requires strong full-stack capabilities, upfront architecture, and proficiency with AI tools like Copilot and Azure AI Foundry. You will contribute to continuous improvement and AI-driven productivity.

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 is 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.

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.

Skills

Full-stack development

AI-assisted delivery

Agile/DevOps

Requirements articulation

Education

Bachelor's degree in CS/Engineering

Tools

GitHub Enterprise

GitHub Copilot

Azure AI Foundry

Copilot SDK

Semantic Kernel

Job description

Role Description

The AI Engineer (Full Stack Engineering) designs, develops, tests, deploys, and maintains modern cloud-native applications using an AI-first engineering model. This 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 is 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 Application Insights, Elastic, logging, and monitoring.