About US
We're building the first end-to-end solution to transform the trades, a trillion-dollar global industry that's been underserved by technology for far too long. Recognized by Forbes as one of the top cloud companies, we use our deep industry knowledge and technical expertise to develop solutions that empower everyday entrepreneurs to grow and scale their businesses. While our vision is bold, we always stay humble. Join us. We're just getting started.
What you'll do
- Take end to end ownership of the short and long term technical vision
- Provide technical mentorship and guidance to engineers within your team and others
- Help your team to improve the technical quality of their work through regular technical design and code reviews
- Be responsible for all major technical decisions for your squad (a successful lead will be able to influence the decisions of their team without having to make all of them)
- Share your technical knowledge and expertise through regular tech talks and/or blog posts
- Communicate effectively with engineers, product managers, customers, partners, and other leaders
What you'll need
- We expect that as an individual contributor, you are a role model
- You will be expected to guide the technology decisions of your team, while contributing alongside them
- Equivalent of 8+ years of experience on senior engineering roles (designing APIs, abstractions, and tools used by other engineers)
- Expert-level knowledge of:
- Microsoft .NET technology stack (C#/JAVA/ .NET, ASP.NET MVC, Web APIs) and SQL databases (Postgres, Microsoft SQL Server or any other)
- HTML5 and JavaScript; experience with Typescript and React is a plus
- Git, unit testing, debugging, profiling, performance monitoring
- Strong communication and technical writing skills
- B.S., B.Tech, M.S., M.Tech, or PhD in Computer Science or equivalent education
- Hands-on, daily experience using AI coding assistants (Cursor, GitHub Copilot, Claude Code, or similar) to write, refactor, debug, or review code
- Working understanding of how LLMs function at a practical level (context windows, prompting, hallucination risks, strengths/limitations) — enough to use them effectively and evaluate their output critically, not academic ML expertise
- General awareness of current AI trends and tools relevant to software engineering, and genuine interest in keeping that knowledge current
- Track record of leading technical projects end-to-end with minimal oversight, including ambiguous, cross-team initiatives
- Strong code review discipline and a demonstrated history of setting or raising engineering quality bars on a team
- Strong communication skills — able to explain technical tradeoffs to both engineers and non-technical stakeholders
- Experience mentoring other engineers and influencing engineering culture and practices
Nice to Have:
- Experience integrating AI/LLM APIs into product features (even at a basic, API-consumption level)
- Familiarity with prompt engineering basics for coding or productivity use cases
- Experience establishing or improving AI-tool usage guidelines/policies on an engineering team
- Experience with cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes)
- Contributions to internal tooling, developer experience, or engineering productivity initiatives
