AI Software Engineer Full Time

W2 OR H1 Transfer ONLY

NEED 11+ YEARS EXPERIENCE

We are seeking an AI Software Engineer to help transform how software is built, tested, and delivered. This role is for a strong software engineer who can use GenAI and agentic development tools as a force multiplier across the software development lifecycle.

You will design and build high-quality software while using AI tools to accelerate coding, testing, refactoring, debugging, documentation, and modernization. You will be expected to guide AI agents effectively, validate their output rigorously, and ensure all delivered software meets enterprise standards for security, quality, performance, and maintainability.

The ideal candidate has strong software engineering fundamentals, hands-on coding experience, and proven ability to use AI tools to materially improve engineering productivity.

Responsibilities include:

• Design, build, test, and maintain software applications.

• Use GenAI tools to accelerate coding, testing, documentation, and debugging.

• Create clear prompts, task definitions, and acceptance criteria for AI agents.

• Review and validate AI-generated code for correctness, quality, security, and maintainability.

• Generate and improve unit, integration, and regression tests using AI.

• Refactor and modernize existing codebases using AI-assisted workflows.

• Participate in architecture, design, code reviews, and production support.

• Continuously improve AI-enabled engineering practices across the team.

Required skills:

• Strong programming skills in Java, Python, JavaScript/TypeScript, Go, C#, or similar.

• Strong computer science and software engineering fundamentals.

• Experience with APIs, databases, cloud platforms, CI/CD, and automated testing.

• Hands-on experience with GenAI coding tools.

• Ability to evaluate and improve AI-generated code.

• Strong understanding of secure and maintainable software design.

Preferred skills:

• Experience with agentic coding tools.

• Experience with legacy modernization.

• Experience in cloud-native engineering.

• Experience in regulated enterprise environments.

• Experience measuring productivity and quality improvements from AI-assisted development.