• Lead the architectural design and technical direction of complex, large-scale systems across the R&D organization, ensuring solutions are scalable, maintainable, and aligned with long-term product strategy • Partner closely with Product Management, UX, and QA teams throughout the full development lifecycle to translate business requirements into sound technical designs and actionable engineering plans • Establish and enforce engineering standards, best practices, and architectural patterns across the engineering team to ensure consistency, quality, and operational excellence at every stage of development • Drive the end-to-end execution of high-priority technical initiatives by identifying risks early, removing blockers, and keeping cross-functional stakeholders informed and aligned throughout delivery • Conduct thorough architecture and code reviews on a regular basis, providing constructive, high-quality feedback that raises the technical bar and accelerates the growth of engineers at all levels • Mentor and guide senior and mid-level engineers through complex technical challenges, serving as a go-to resource for architectural guidance and engineering decision-making across the organization • Evaluate emerging technologies, tools, and industry trends on an ongoing basis and make informed recommendations that strengthen the engineering platform, improve developer productivity, and support the company's technical roadmap

- Absolute Domain Ownership: Take responsibility for a specific part of the platform or product. You will shape the technical direction, write and review production code, maintain CI/CD pipelines, prepare releases, and make sure your area is stable in production. - Rapid Prototyping: Turn ideas, experiments, or unclear requirements into working solutions. Use AI tools where they help speed up routine work, such as drafting technical specs, creating tests, refactoring, or planning implementation. - Smart Scaling: Identify technical bottlenecks in your area and lead the changes needed to fix them. This may include architecture improvements, infrastructure changes, cloud-related work, or better observability. - Daily orchestration: Use tools like Claude Code, or similar assistants as part of your development process. This may include debugging, writing tests, refactoring legacy code, improving documentation, or exploring unfamiliar parts of the codebase. - Validation & integrity: You act as the "Interception Layer." You validate AI outputs to ensure your domain doesn't drift into "Dark Architecture" or "AI Slop." - Connect product needs with engineering execution: Work with stakeholders to understand business needs and turn them into clear technical plans. Help prioritize work based on impact, risk, and technical complexity, and push back on work that does not bring enough value. - Keep ownership clear and execution focused: Stay close to how your work behaves in production. Help with incidents, improve monitoring and observability, and reduce unnecessary process overhead where possible.

• Design and develop AI-powered product features with a focus on LLM-based capabilities • Build and maintain MCP servers and agent-based components • Develop enterprise-grade web services and backend integrations • Work with tools, data sources, and model interfaces across cloud environments • Collaborate with engineering teams to deliver production-ready AI solutions

• Design and develop AI-powered product features with a focus on LLM-based capabilities • Build and maintain MCP servers and agent-based components • Develop enterprise-grade web services and backend integrations • Work with tools, data sources, and model interfaces across cloud environments • Collaborate with engineering teams to deliver production-ready AI solutions