AI-First Software Engineer

Position Overview

The AI-First Software Engineer is responsible for designing, developing, testing, and deploying high-quality production software across a multi-product technology platform. This role embraces AI-assisted software development as a core part of the engineering workflow, using tools such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining strong standards for code quality, security, testing, and maintainability.

Working closely with fellow engineers and senior technology leadership, including the Chief Technology Officer (CTO), the AI-First Software Engineer will contribute to high-impact initiatives, support the development of scalable software solutions, and help establish best practices for AI-driven engineering across the organization. The role primarily operates within the .NET ecosystem while offering opportunities to contribute to applications and services built on other technology stacks.

The ideal candidate is a strong software engineer with a proven track record of shipping production code, practical experience using AI coding tools, sound engineering judgment, and the ability to adapt quickly in a collaborative, fast-paced environment.

Key Responsibilities

Software Design & Development

• Design, develop, test, and deploy reliable, scalable, and maintainable software across multiple products and applications.
• Translate business requirements and technical specifications into effective software solutions.
• Contribute to the full software development lifecycle, including technical design, implementation, testing, deployment, monitoring, and ongoing maintenance.
• Develop and maintain backend services, APIs, application components, and integrations that support business-critical functionality.
• Work primarily within the .NET ecosystem, including C# and related technologies, while contributing to applications built on other technology stacks as needed.
• Write clean, readable, reusable, and well-documented code that follows established engineering standards and architectural patterns.
• Identify opportunities to improve application performance, reliability, scalability, and maintainability.
• Troubleshoot production issues, diagnose root causes, and implement effective solutions.
• Participate in technical design discussions and contribute to architectural decisions that support long-term product growth.

AI-First Software Engineering

• Integrate AI coding assistants, particularly Cursor, into daily development workflows to improve productivity and accelerate software delivery.
• Use AI tools throughout the development lifecycle, including requirements analysis, code generation, refactoring, debugging, test creation, documentation, and code review preparation.
• Apply sound engineering judgment to evaluate AI-generated code for correctness, security, performance, maintainability, and alignment with project requirements.
• Validate AI-generated solutions through appropriate testing, debugging, code review, and technical analysis before merging or deploying changes.
• Develop and refine effective prompts, reusable workflows, and AI-assisted development practices that improve consistency and engineering efficiency.
• Identify tasks that benefit from AI assistance while recognizing when manual implementation, deeper investigation, or alternative approaches are more appropriate.
• Stay current with emerging AI development tools, capabilities, limitations, and best practices.
• Help establish standards for responsible and effective AI-assisted software development across the engineering organization.

Code Quality, Testing & Reliability

• Write unit tests, integration tests, and other automated tests to validate application behavior and prevent regressions.
• Ensure AI-assisted code meets established quality, reliability, and security requirements before release.
• Participate in peer code reviews, providing constructive feedback and incorporating feedback from teammates.
• Identify and address technical debt, defects, and opportunities to simplify existing code.
• Follow secure coding practices and help protect applications, data, and services from potential vulnerabilities.
• Support continuous integration and continuous delivery processes to enable reliable and repeatable software releases.
• Investigate production defects and implement corrective actions to prevent recurring issues.
• Maintain appropriate technical documentation, test coverage, and development standards.

Multi-Product Platform Development

• Contribute to software products and services that support a broad technology platform, including property management, accounting, customer relationship management, payments, tenant screening, and related business functions.
• Adapt to different codebases, architectures, and development environments as business priorities require.
• Build and maintain APIs, integrations, and shared components that enable products to work together effectively.
• Understand existing system architecture and business logic before introducing changes to established applications.
• Collaborate with engineers across product teams to deliver consistent, reliable functionality.
• Identify opportunities to reuse components, improve interoperability, and reduce unnecessary duplication across products.
• Balance rapid delivery with the need to maintain stable, secure, and scalable software.

Collaboration & Technical Communication

• Work closely with fellow engineers, product stakeholders, and the CTO on high-priority technical initiatives.
• Participate in technical planning, design reviews, code reviews, and team discussions.
• Communicate implementation approaches, technical risks, dependencies, and progress clearly.
• Collaborate with cross-functional teams to clarify requirements, evaluate trade-offs, and deliver solutions that meet business needs.
• Share successful AI-assisted development techniques, prompts, workflows, and lessons learned with the broader engineering organization.
• Contribute to a culture of experimentation, knowledge sharing, accountability, and continuous improvement.
• Provide technical guidance and support to teammates when appropriate.

Engineering Productivity & Continuous Improvement

• Identify opportunities to streamline development workflows, reduce repetitive tasks, and improve engineering productivity through AI and automation.
• Experiment with AI-assisted approaches to software design, debugging, testing, documentation, and maintenance.
• Evaluate the effectiveness of new tools and workflows based on measurable improvements in delivery speed, quality, and reliability.
• Help document and standardize effective development practices so they can be adopted across teams.
• Recommend improvements to development tooling, code review processes, testing strategies, and deployment workflows.
• Contribute to technical initiatives that improve developer experience and support the organization's broader AI adoption strategy.

Qualifications

Education & Professional Experience

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field preferred; equivalent practical experience will also be considered.
• Proven experience developing and shipping production-quality software in a professional engineering environment.
• [X+ years] of professional software development experience, with the required level to be determined based on the role's seniority.
• Demonstrated experience contributing to the full software development lifecycle, from technical design through deployment and maintenance.
• Experience working with existing production systems, debugging complex issues, and delivering reliable software changes.
• A portfolio of meaningful engineering contributions demonstrating technical proficiency, problem-solving ability, and software delivery experience.

Technical Skills

• Strong proficiency in at least one modern programming language and experience building production applications.
• Experience with C# and the .NET ecosystem is a significant advantage, although strong engineers from other technology stacks are encouraged to apply.
• Understanding of software architecture, object-oriented programming, data structures, algorithms, and common design patterns.
• Experience developing and consuming REST APIs, working with databases, and integrating software systems.
• Familiarity with relational databases, SQL, data modeling, and application performance optimization.
• Experience with Git or similar version control systems and collaborative development workflows.
• Understanding of automated testing, code review, debugging, and software quality practices.
• Familiarity with CI/CD pipelines, cloud infrastructure, containerization, or modern deployment practices is an advantage.
• Ability to learn unfamiliar technologies and navigate multiple codebases effectively.

AI Development Experience

• Hands-on experience using AI coding assistants such as Cursor, GitHub Copilot, Claude Code, or comparable tools in real-world software development.
• Demonstrated ability to use AI tools to accelerate implementation, refactoring, debugging, testing, or documentation.
• Strong judgment in reviewing AI-generated code and identifying incorrect assumptions, logic errors, security concerns, and potential performance issues.
• Ability to validate AI-generated output through testing, code analysis, and independent technical reasoning.
• Interest in developing repeatable AI-assisted engineering workflows and sharing effective practices with teammates.
• Willingness to adapt as AI development tools and engineering practices continue to evolve.

Preferred Qualifications

• Experience in property technology (PropTech), software-as-a-service (SaaS), payments, property management, or other complex business software environments.
• Experience working across multiple products, services, or technology stacks.
• Familiarity with cloud platforms such as Microsoft Azure or Amazon Web Services (AWS).
• Experience with distributed systems, microservices, event-driven architectures, or large-scale application integrations.
• Experience building developer tools, internal automation, or AI-assisted development workflows.
• Familiarity with application monitoring, observability, performance profiling, and production support.
• Experience working closely with senior engineering leaders or contributing to high-visibility technical initiatives.

Professional & Interpersonal Skills

• Strong analytical thinking and problem-solving skills, with the ability to evaluate complex technical challenges.
• Excellent engineering judgment and attention to detail.
• Ability to balance development speed with software quality, security, and long-term maintainability.
• Strong written and verbal communication skills.
• Collaborative mindset and willingness to share knowledge, receive feedback, and contribute to team success.
• Comfortable working in a fast-paced environment with evolving priorities and direct access to senior leadership.
• Self-directed approach to learning, experimentation, and continuous professional development.
• Ability to manage competing priorities and deliver reliable results within agreed timelines.