Senior Software Engineer - .NET + AI

About Zenoti

Role overview

What you will do

• Own end-to-end development and technical success of significant product-module features.
• Build scalable SaaS applications using .NET/C#, REST APIs, SQL/NoSQL, and Flutter or React.
• Resolve technical ambiguity and plan and estimate work for owned features.
• Design extensible, testable components, make architectural decisions, and lead technical design reviews.
• Drive testing standards and coverage and help improve test automation infrastructure.
• Ensure compliance with applicable regulatory and data governance requirements and apply security-first design, including threat modeling.
• Collaborate with Product Managers, Designers, and Engineers to deliver customer-focused features in an agile environment.
• Own production health through monitoring, alerts, dashboards, and incident response for developed components.
• Use AI-assisted development tools for design, implementation, debugging, testing, documentation, and code review.
• Review AI-generated output critically, especially for security, data integrity, architecture, compliance, and customer-critical workflows.
• Write design documents and communicate technical decisions and trade-offs to technical and non-technical audiences.

Skills and experience

• 5–7 years designing and building enterprise-scale SaaS applications using Microsoft technologies, including .NET/C#, REST APIs, SQL Server/NoSQL, and Flutter or React.
• 3+ years building highly available, scalable distributed cloud services using AWS or Azure.
• Strong system design, analytical thinking, and problem-solving skills, with ability to own complex technical problems.
• Production experience using AI-assisted development tools such as Copilot, Claude Code, or Cursor.
• Strong judgment in reviewing AI-generated code for security, performance, scalability, reliability, and data integrity.
• Excellent communication and collaboration skills; comfortable in a fast-paced, evolving product organization.
• Experience with developer productivity tooling, prompt libraries, reusable workflows, MCP servers, or AI-enabled engineering automation is a plus.
• Interest in learning and applying emerging AI-assisted engineering practices that create measurable value.