GenAI Engineer

Job Summary:
We are seeking a highly skilled GenAI Engineer with hands-on experience in Devin AI, Claude Code, and AI-assisted software engineering to accelerate software development through intelligent automation. The ideal candidate will partner with engineering teams to design, develop, test, and deploy enterprise applications while leveraging AI coding agents to improve productivity, code quality, and delivery speed. This role requires strong software engineering fundamentals, cloud-native development experience, CI/CD expertise, and a passion for building reusable AI engineering assets.

Key Responsibilities:
Design, develop, test, and deploy enterprise software solutions in collaboration with engineering teams.
Leverage Devin AI, Claude Code, GitHub Copilot, or similar AI coding assistants to accelerate software development, testing, debugging, documentation, and modernization initiatives.
Create and maintain reusable AI assets including Devin Playbooks, Knowledge Assets, CLAUDE.md files, Skills, Hooks, and workflow templates.
Contribute to repository onboarding and AI workflow standardization across engineering teams.
Collaborate with architects, product owners, QA teams, and developers to deliver scalable, high-quality software solutions.
Ensure AI-generated code complies with engineering best practices, security standards, quality guidelines, and organizational compliance requirements.
Continuously evaluate and improve AI-assisted software development workflows and engineering practices.
Promote AI engineering best practices and share reusable assets across multiple teams.
Support DevOps initiatives, CI/CD automation, and cloud-native application development.
Required Qualifications
Bachelor's degree in Computer Science, Software Engineering, or related field.
Strong experience in software engineering and enterprise application development.
Hands-on experience with Devin AI, Claude Code, GitHub Copilot, or similar AI-assisted development platforms.
Strong knowledge of modern software development methodologies and Agile practices.
Experience with CI/CD pipelines, automated testing, and cloud-native application development.
Experience developing APIs and microservices.
Strong understanding of software architecture, design patterns, and engineering best practices.
Excellent analytical, communication, and collaboration skills.
Passion for AI-assisted engineering and developer productivity improvements.

Preferred Qualifications:
Experience with Agentic AI development.
Experience building Generative AI applications.
Knowledge of Retrieval-Augmented Generation (RAG).
Experience with Prompt Engineering and Context Engineering.
DevOps and Platform Engineering experience.
Experience with workflow automation frameworks.
Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.