Engineering Manager

Sunset Engineering ManagerAt its core, Sunset was founded to help founders. We started by supporting startups through shutting down, but we have since expanded into unlocking a new revenue stream for all types of businesses.In 2025, we had a unique insight: the data every company generates each day through collaboration, communication, and building is some of the most valuable training data in the world. Public and synthetic data can only get frontier models so far, so the next generation of model progress depends on real, proprietary data grounded in how actual businesses operate. We are a primary source of it, partnering directly with the frontier AI labs building what comes next.The engineering work spans some of the messiest parts of enterprise data: getting internal work data out of the systems where it lives, helping companies navigate dissolution, and de-identifying sensitive datasets without destroying what makes them useful. Doing this well requires thoughtful product interfaces, long-running workflows, data and ML systems, evaluation, permissions, and reliable operations to work as one system.You will build a high-agency engineering team, develop strong independent owners, and turn difficult customer and technical problems into trustworthy products and systems.This is an opportunity to shape the team and its technical operating system, not inherit layers of established process. You will influence who we hire, how ownership is divided, which capabilities become durable infrastructure, how we evaluate quality, and how AI changes the way the team builds.This is a bounded player-coach role. Management is the primary job, but you will stay technically active through design and code review, debugging, incidents, prototypes, and occasional implementation where it creates leverage. You will not carry a standing feature load or become the owner of roadmap-critical implementation.ResponsibilitiesHire, onboard, coach, and develop engineers into strong independent ownersDefine ownership and technical direction across the product and systems your team is responsible forTurn customer behavior, product usage, data quality, system health, and team evidence into a sequenced roadmapReview important designs and pull requests, debug difficult failures alongside the team, and lead technical decisions and incidents when neededPrototype or contribute code selectively when it resolves ambiguity, unblocks the team, or creates reusable leverageEstablish lightweight practices for planning, evaluation, releases, incidents, quality, and learningDelegate meaningful decisions without becoming detached from the technical workLead difficult production and customer situations without creating a hero cultureMake security, privacy, permissions, AI behavior, and recovery part of product and engineering designUse AI engineering tools directly and establish team practices for speed, review, evaluation, and verificationSuccess IndicatorsEngineers understand what they own and make strong product and technical decisions without waiting for youNew hires ramp quickly, senior ICs grow, and new leaders emergeGet Data journeys become more complete, observable, and recoverable, with fewer recurring escalations and less manual rescueClean Data deliveries become easier to evaluate and investigate, with fewer escaped defects, avoidable reruns, and ambiguous failuresThe team can distinguish product, source-data, model, evaluation, orchestration, and infrastructure failures—and fix their recurring causesAI improves engineering and product capability without weakening quality, security, or human judgmentDelivery becomes more predictable while customer trust, system reliability, and the team's capacity increaseYour technical involvement improves the team's judgment and independence rather than making delivery depend on youQualificationsYou have at least two years of experience directly managing engineers who build production softwareYou have hired well, delivered direct feedback, handled performance issues, and developed senior engineers into broader ownersYou have built or led technically demanding products involving complex workflows, data systems, AI/ML, infrastructure, or sensitive informationYou can review code and designs with depth, debug alongside the team, prototype when useful, and step back once ownership is clearYou use AI engineering tools fluently and have a practical point of view about where they create leverage, where they fail, and how their work should be verifiedYou have startup experience and enjoy broad ownership, changing context, and incomplete informationYou communicate clearly with customers, Product, Design, domain experts, and highly technical ICsNot a FitYou want a people-management role that stays removed from product and technical decisionsYou want your ongoing contribution to be a standing feature workload or critical-path implementationYou prefer adding process before understanding the product, system, and ownership problem directlyYou need clean boundaries between product, engineering, data, AI, and customer workYou are most comfortable being the permanent decision-maker rather than developing ownership in othersYou do not want AI tools to be part of your own or your team's daily engineering workflowBonusExperience leading teams that span software, data, ML, evaluation, or infrastructureExperience with enterprise data connections, workflow-heavy products, or internal toolsExperience with de-identification, privacy-sensitive data, compliance, or otherwise high-trust productsExperience establishing evaluation, incident, release, or quality systems that improved outcomes without adding heavy ceremonyExperience growing an engineering organization through an early-stage or high-change period