{"id":116923,"url":"https://alion.io/job/sunset-engineering-manager","title":"Engineering Manager","company":{"id":28307,"name":"Replay","domain":"replay.ai","url":"https://alion.io/company/replay","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":100,"open_postings":13,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":215000,"max_usd":439000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1203},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-08-13T19:39:21Z","employer_posted_date":"2026-08-13","last_verified_at":"2026-10-17T08:59:41Z","board_verified":true,"closed_at":null,"days_open":64,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":64},"description":"About Replay\nAt its core, Replay 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.\nIn 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.\nWhy Join Replay Now\nWe have scaled from $0 to a multi-eight-figure run rate in a matter of months\n\nWe have raised from top-tier investors, including Floodgate, Afore, Ludlow, and Hustle Fund\n\nWe are small enough that you will carry outsized responsibility and grow as quickly as the company does\n\nYou will partner with and build for some of the fastest and most important companies in the world\n\nYou will help build a massive, category-defining business from the ground floor\n\nThe Role\nThe 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.\nYou will build a high-agency engineering team, develop strong independent owners, and turn difficult customer and technical problems into trustworthy products and systems.\nThis 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.\nThis 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.\nWhat You'll Do\nHire, onboard, coach, and develop engineers into strong independent owners\n\nDefine ownership and technical direction across the product and systems your team is responsible for\n\nTurn customer behavior, product usage, data quality, system health, and team evidence into a sequenced roadmap\n\nReview important designs and pull requests, debug difficult failures alongside the team, and lead technical decisions and incidents when needed\n\nPrototype or contribute code selectively when it resolves ambiguity, unblocks the team, or creates reusable leverage\n\nEstablish lightweight practices for planning, evaluation, releases, incidents, quality, and learning\n\nDelegate meaningful decisions without becoming detached from the technical work\n\nLead difficult production and customer situations without creating a hero culture\n\nMake security, privacy, permissions, AI behavior, and recovery part of product and engineering design\n\nUse AI engineering tools directly and establish team practices for speed, review, evaluation, and verification\n\nWhat Success Looks Like\nEngineers understand what they own and make strong product and technical decisions without waiting for you\n\nNew hires ramp quickly, senior ICs grow, and new leaders emerge\n\nGet Data journeys become more complete, observable, and recoverable, with fewer recurring escalations and less manual rescue\n\nClean Data deliveries become easier to evaluate and investigate, with fewer escaped defects, avoidable reruns, and ambiguous failures\n\nThe team can distinguish product, source-data, model, evaluation, orchestration, and infrastructure failures-and fix their recurring causes\n\nAI improves engineering and product capability without weakening quality, security, or human judgment\n\nDelivery becomes more predictable while customer trust, system reliability, and the team's capacity increase\n\nYour technical involvement improves the team's judgment and independence rather than making delivery depend on you\n\nYou Might Thrive Here If\nYou have at least two years of experience directly managing engineers who build production software\n\nYou have hired well, delivered direct feedback, handled performance issues, and developed senior engineers into broader owners\n\nYou have built or led technically demanding products involving complex workflows, data systems, AI/ML, infrastructure, or sensitive information\n\nYou can review code and designs with depth, debug alongside the team, prototype when useful, and step back once ownership is clear\n\nYou 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 verified\n\nYou have startup experience and enjoy broad ownership, changing context, and incomplete information\n\nYou communicate clearly with customers, Product, Design, domain experts, and highly technical ICs\n\nThis Role May Not Be for You If\nYou want a people-management role that stays removed from product and technical decisions\n\nYou want your ongoing contribution to be a standing feature workload or critical-path implementation\n\nYou prefer adding process before understanding the product, system, and ownership problem directly\n\nYou need clean boundaries between product, engineering, data, AI, and customer work\n\nYou are most comfortable being the permanent decision-maker rather than developing ownership in others\n\nYou do not want AI tools to be part of your own or your team's daily engineering workflow\n\nBonus\nExperience leading teams that span software, data, ML, evaluation, or infrastructure\n\nExperience with enterprise data connections, workflow-heavy products, or internal tools\n\nExperience with de-identification, privacy-sensitive data, compliance, or otherwise high-trust products\n\nExperience establishing evaluation, incident, release, or quality 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