Job Title: AI-Native Staff Engineer - SN
Location: 100% Remote
Employment: W2Role OverviewThis role operates within an AI-native delivery model where engineers use Claude to generate large volumes of production-bound code across the full stack, then own, review, and make that code production-ready.
The Staff Engineer (AI) is a senior individual contributor who also guides a small team and is responsible for building production software using AI-native development workflows as part of a small, focused AI-Native team.
This role works closely with other team engineers to rapidly design, implement, test, and iterate on high-quality software.
AI Orchestrators (another term used for AI Engineers) are strong engineers who use AI tools as a first-class part of their daily engineering workflow to accelerate development, improve testing, and shorten feedback loops.
This role is not focused on training AI models or building machine learning pipelines. It focuses on building software efficiently, safely, and at high quality using AI-assisted engineering practices.
Key Responsibilities1. AI-Native Software Development - 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.
2. Application Design and Implementation - 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.
3. AI Orchestration and Workflow Execution - 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.
4. Collaboration and Team Execution - 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.
Technical Skills and Requirements - AI-Assisted Development Tools: Experience with Claude, GitHub Copilot, or equivalent AI coding tools is required.
- Programming Language: Java.
- Database Design: Experience with Oracle and PostgreSQL.
- Software Engineering: Experience building production-grade software across backend services, frontend components, APIs, workflows, and test code.
- AI-Native Engineering Practices: Ability to use AI tools effectively for code generation, testing, debugging, refactoring, and documentation, while ensuring production readiness.
Additional Notes - AI-tooling experience is required.
- Code generation spans backend services, frontend components, APIs, workflows, and test code.
- The role emphasizes production software engineering using AI-assisted development practices rather than AI model training or machine learning pipeline development.
