AI-Native Full Stack Engineer

Position overview: We are looking for an AI-Native Full Stack Engineer to support the development and evolution of the client’s ecosystem. In this role, you will design, develop, test, and deliver cloud-native applications while using AI-assisted engineering practices throughout the software development lifecycle.

The ideal candidate is a strong full-stack engineer who uses AI tools and automation as part of their daily workflow and can contribute across frontend, backend, cloud, integration, and DevOps activities.

The estimated salary range for this position is USD 150,000 to 180,000 per year.

Responsibilities: Develop and maintain frontend and backend platform capabilities

Build secure, scalable, cloud-native applications

Participate in architecture discussions, design reviews, code reviews, and production support

Use AI-native development practices to improve productivity, delivery speed, and quality

Create automated test coverage and technical documentation

Collaborate with product, architecture, security, and platform teams

Support integration with enterprise systems and services

Contribute to monitoring, troubleshooting, and the continuous improvement of engineering practices

Requirements: Strong experience as a Full Stack Engineer building cloud-native applications with React, TypeScript, Next.js, Java, Spring Boot, and Node.js.

Hands-on experience designing and developing REST APIs, microservices, and responsive, accessible user interfaces.

Solid knowledge of SQL and NoSQL databases, such as PostgreSQL and MongoDB.

Experience with AWS services, Docker, CI/CD pipelines, GitHub Actions, and Infrastructure as Code, preferably with Terraform.

Strong understanding of OAuth/OIDC, JWT authentication, secure coding practices, API integrations, and enterprise integration patterns.

Daily use of AI development tools such as GitHub Copilot, Cursor, Claude Code, or equivalent tools as part of the software delivery workflow.

Experience with AI-assisted coding, testing, debugging, documentation, and prompt engineering.

Experience in LMS, EdTech, AI-powered products, skills assessment platforms, simulation-based learning, or enterprise SaaS solutions is a plus.