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Sunset is a rapidly scaling business process automation platform that helps companies unlock value from their internal data. Founded to support startup dissolution, the company has pivoted to become a primary source of proprietary training data for frontier AI labs, scaling from zero to multi-eight-figure run rate in months with backing from top-tier investors including Floodgate and Afore.
As Engineering Manager, you will build and lead a high-agency engineering team tackling some of enterprise data's messiest challenges: extracting internal work data from legacy systems, supporting company dissolution processes, and de-identifying sensitive datasets while preserving their utility. The role requires integrating thoughtful product interfaces, long-running workflows, data and ML systems, evaluation frameworks, permissions, and reliable operations into cohesive systems.
You will shape the team's technical operating system from the ground floor, influencing hiring decisions, ownership structures, infrastructure priorities, quality evaluation, and how AI augments engineering practices. This is a bounded player-coach role where management is primary but you remain technically active through design review, code review, debugging, incident response, prototyping, and selective implementation where it creates leverage. You will not carry standing feature loads or own critical-path implementation.
Key responsibilities include hiring and developing engineers into strong independent owners, defining technical direction and ownership, translating customer behavior and system health into sequenced roadmaps, reviewing designs and pull requests, debugging failures alongside the team, establishing lightweight practices for planning and evaluation, and making security, privacy, permissions, and AI behavior integral to product design. You'll use AI engineering tools directly and establish team practices for speed, review, and verification.
Success means engineers understand their ownership and make strong decisions independently, new hires ramp quickly, senior ICs grow, data journeys become more complete and observable with fewer escalations, deliveries become predictable while reliability increases, and your technical involvement strengthens team judgment rather than creating dependency.
You should have at least two years directly managing engineers building production software, proven hiring and feedback skills, experience with technically demanding products involving complex workflows, data systems, AI/ML, or sensitive information, and startup experience with comfort in broad ownership and incomplete information. Fluency with AI engineering tools and clear communication across technical and non-technical stakeholders is essential.
