VP of Engineering (Remote)

About CrystalCrystal Intelligence is a blockchain analytics and compliance intelligence company serving exchanges, financial institutions, regulators, and law enforcement across 100+ blockchains. Our customers depend on us for low-latency, high-availability risk and transaction intelligence that powers operational decisions.Crystal is entering the most consequential platform shift in its history: a full migration from our current data architecture to a new, AI-native data pipeline that will define the company's next decade of scale, speed, and product capability. This is the role that owns it.Role SummaryCrystal's engineering organization has grown organically. The current architecture serves a large and loyal customer base, but it is reaching the limits of what feature-driven growth can sustain. In parallel, we have built a new data pipeline architecture led by a dedicated platform team.The strategic priority for 2026 is to migrate Crystal end-to-end from the legacy stack to the new pipeline - without disrupting customer SLAs, while continuing to ship the product roadmap, and while rebuilding engineering management discipline. The VP of Engineering will own this migration.The mission is concrete: deliver the new pipeline into production behind every Crystal product, restore platform-grade latency and reliability, and convert the existing organization into one that ships predictably and uses AI as a productivity multiplier.What You’ll DoOwn the platform migration end-to-endLead the integration of the new data pipeline into all Crystal products: Crystal Expert, Crystal Foresight, Monitor, Risk Check API, Data Intelligence, and Crystal LightSequence the migration to preserve revenue and customer trust: no SLA regressions, no rollback drama, no surprise downtimeDrive the architectural decisions and trade-offs that the legacy-to-new transition requires, including data model alignment, service-by-service cutover, and parallel-run validationHold engineering, product, and customer success aligned on a single migration roadmap with clear customer-impact gatesRestore platform foundationsBring API and core platform latency back to target: 1,000 RPS at sub-two-second latency, scaling toward 10k RPSReduce database load, fix stability regressions exposed by recent releases, raise release velocity to multiple deployments per weekLead the multi-chain platform with discipline across 100+ chains: predictable integration timelines, accountable squad ownership, clear SLAs to commercial partnersRebuild the engineering management layerPartner with the existing engineering leadership to establish clear accountability across squad leads, engineering managers, and platform teamsSet the standard for what good engineering management looks like at Crystal: predictable delivery, transparent planning, technical depth, people developmentMake the hiring, performance, and structural decisions required to bring the organization to the level the platform demandsDrive AI into engineering as a productivity leverBuild shared infrastructure for AI-assisted engineering: code generation, automated testing, agent-based migration tooling, internal knowledge systemsMove Crystal from individual AI tool usage to organization-wide AI productivity, with measurable impact on delivery throughputReduce OpEx-to-revenue through architectural improvements, automation, and reduction of manual operational loadPartner with the businessWork directly with product, GTM, customer success, and finance to translate engineering investments into customer outcomes and revenueCommunicate trade-offs, risks, and progress clearly to the executive team and boardOwn the engineering budget, hiring plan, and vendor decisionsWhat Success Looks Like (12 Months)New data pipeline architecture is in production powering Crystal's core productsCustomer SLAs are met or exceeded throughout the migration; no customer churn attributable to platform instabilityLatency restored and improved; release cadence shifted from monthly to weekly or fasterEngineering management layer operating with clear accountability and predictable deliveryAI-assisted engineering infrastructure deployed and measurable productivity gains realizedOpEx-to-revenue ratio meaningfully reduced toward targetRequirements10+ years engineering experience, with 5+ years leading platform, data, or infrastructure organizations as VP Engineering, Head of Engineering, or equivalentLed at least one major platform migration or large-scale rebuild, with continuous customer service maintained throughoutOperated low-latency, high-availability distributed systems with multi-tenant SaaS workloads at production scaleProduction experience integrating AI into engineering workflows, including agent-assisted development and AI-driven automationStrong product partnership instincts - you have shaped what gets built and how it shipsTrack record of building accountable, high-ownership engineering organizationsDirect experience in one or more relevant domains: blockchain or crypto, fintech, payments, fraud or risk platforms, regulatory technology, or large-scale data platforms