Staff Software Engineer – AI-Native Development

Katalyst CRO is recruiting for a confidential client. The Staff Software Engineer will build and enhance production software using AI-assisted development workflows, review AI-generated code for production readiness, and guide a small AI-Native team in delivering software end-to-end.

Responsibilities:

• Build and enhance production-grade software applications using AI-assisted development workflows
• Translate product and technical requirements into working, maintainable software
• Use AI tools to accelerate coding, debugging, testing, refactoring, and documentation
• Review, validate, and refine AI-generated code to ensure correctness, performance, security, and maintainability
• Design and implement clean, well-structured APIs, services, and application components
• Contribute to scalable backend systems and full-stack solutions as required by the team
• Apply sound engineering judgment to balance speed, quality, and long-term maintainability
• Participate in design discussions and technical reviews within the team
• Orchestrate the effective use of AI tools across development activities, including:
• Code generation and refactoring
• Test creation and validation
• Debugging and issue analysis
• Documentation and design artifacts
• Follow and help refine AI-native engineering standards established by the Tech Lead
• Contribute feedback and improvements to AI-assisted workflows and development practices
• Collaborate closely with the AI-Native Tech Architect(s) to implement architectural and engineering best practices
• Work effectively within a small AI-Native team to deliver features end-to-end
• Coordinate with adjacent teams as needed for integration, dependencies, and shared services
• Communicate technical issues and trade-offs clearly to engineering and product stakeholders

Requirements:

• Experience with Claude, GitHub Copilot, or equivalent AI coding tools is required
• Java
• Experience with Oracle and PostgreSQL
• Experience building production-grade software across backend services, frontend components, APIs, workflows, and test code
• Ability to use AI tools effectively for code generation, testing, debugging, refactoring, and documentation, while ensuring production readiness