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ServiceTitan is seeking a Staff Corporate Software Engineer to take end-to-end ownership of technical vision and strategy for their engineering organization. In this role, you will serve as a technical leader and mentor, guiding engineers across teams while continuing to contribute hands-on to critical projects.
Key responsibilities include:
- Owning the short and long-term technical vision for your squad and influencing broader technical decisions across the organization
- Providing technical mentorship and guidance to engineers within your team and across the company
- Conducting regular technical design and code reviews to improve code quality and engineering practices
- Leading major technical decisions while empowering your team to own their work
- Sharing technical knowledge through tech talks, blog posts, and documentation
- Communicating effectively with engineers, product managers, customers, partners, and leadership
You will need 8+ years of experience in senior engineering roles, with demonstrated expertise in designing APIs, abstractions, and tools used by other engineers. Required technical skills include expert-level knowledge of the Microsoft .NET stack (C#, ASP.NET MVC, Web APIs), SQL databases (Postgres, SQL Server), HTML5, JavaScript, and modern development practices (Git, unit testing, debugging, performance monitoring).
A critical aspect of this role is hands-on daily experience with AI coding assistants (Cursor, GitHub Copilot, Claude Code) and a working understanding of LLMs—including context windows, prompting, hallucination risks, and practical limitations. You should have genuine interest in current AI trends relevant to software engineering.
You should have a track record of leading technical projects end-to-end with minimal oversight, strong code review discipline, and experience mentoring engineers and influencing engineering culture. Strong communication skills are essential for explaining technical tradeoffs to both technical and non-technical stakeholders.
Nice-to-have qualifications include experience integrating AI/LLM APIs into product features, prompt engineering basics, establishing AI-tool usage guidelines, cloud infrastructure experience (AWS, GCP, Azure), and contributions to developer experience or engineering productivity initiatives.
A B.S., B.Tech, M.S., M.Tech, or PhD in Computer Science or equivalent education is required.
