AI-Native Full Stack Engineer

DataArt · Dallas, TX, US

Spotted 3h ago
Job description

About this role

Employer-provided description, formatted for easier reading.

  • 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.
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