VP of Engineering

<p><strong>About Crystal</strong></p><p>Crystal 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.</p><p>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.</p><p><strong>Role summary</strong></p><p>Crystal'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.</p><p>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.</p><p>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.</p><p><strong>What You’ll Do</strong></p><p><strong>Own the platform migration end-to-end</strong></p><ul><li><p>Lead the integration of the new data pipeline into all Crystal products: Crystal Expert, Crystal Foresight, Monitor, Risk Check API, Data Intelligence, and Crystal Light</p></li><li><p>Sequence the migration to preserve revenue and customer trust: no SLA regressions, no rollback drama, no surprise downtime</p></li><li><p>Drive the architectural decisions and trade-offs that the legacy-to-new transition requires, including data model alignment, service-by-service cutover, and parallel-run validation</p></li><li><p>Hold engineering, product, and customer success aligned on a single migration roadmap with clear customer-impact gates</p></li></ul><p><strong>Restore platform foundations</strong></p><ul><li><p>Bring API and core platform latency back to target: 1,000 RPS at sub-two-second latency, scaling toward 10k RPS</p></li><li><p>Reduce database load, fix stability regressions exposed by recent releases, raise release velocity to multiple deployments per week</p></li><li><p>Lead the multi-chain platform with discipline across 100+ chains: predictable integration timelines, accountable squad ownership, clear SLAs to commercial partners</p></li></ul><p><strong>Rebuild the engineering management layer</strong></p><ul><li><p>Partner with the existing engineering leadership to establish clear accountability across squad leads, engineering managers, and platform teams</p></li><li><p>Set the standard for what good engineering management looks like at Crystal: predictable delivery, transparent planning, technical depth, people development</p></li><li><p>Make the hiring, performance, and structural decisions required to bring the organization to the level the platform demands</p></li></ul><p><strong>Drive AI into engineering as a productivity lever</strong></p><ul><li><p>Build shared infrastructure for AI-assisted engineering: code generation, automated testing, agent-based migration tooling, internal knowledge systems</p></li><li><p>Move Crystal from individual AI tool usage to organization-wide AI productivity, with measurable impact on delivery throughput</p></li><li><p>Reduce OpEx-to-revenue through architectural improvements, automation, and reduction of manual operational load</p></li></ul><p><strong>Partner with the business</strong></p><ul><li><p>Work directly with product, GTM, customer success, and finance to translate engineering investments into customer outcomes and revenue</p></li><li><p>Communicate trade-offs, risks, and progress clearly to the executive team and board</p></li><li><p>Own the engineering budget, hiring plan, and vendor decisions</p></li></ul><p><strong>What Success Looks Like (12 Months)</strong></p><ul><li><p>New data pipeline architecture is in production powering Crystal's core products</p></li><li><p>Customer SLAs are met or exceeded throughout the migration; no customer churn attributable to platform instability</p></li><li><p>Latency restored and improved; release cadence shifted from monthly to weekly or faster</p></li><li><p>Engineering management layer operating with clear accountability and predictable delivery</p></li><li><p>AI-assisted engineering infrastructure deployed and measurable productivity gains realized</p></li><li><p>OpEx-to-revenue ratio meaningfully reduced toward target</p></li></ul><p><strong>Requirements</strong></p><ul><li><p>10+ years engineering experience, with 5+ years leading platform, data, or infrastructure organizations as VP Engineering, Head of Engineering, or equivalent</p></li><li><p>Led at least one major platform migration or large-scale rebuild, with continuous customer service maintained throughout</p></li><li><p>Operated low-latency, high-availability distributed systems with multi-tenant SaaS workloads at production scale</p></li><li><p>Production experience integrating AI into engineering workflows, including agent-assisted development and AI-driven automation</p></li><li><p>Strong product partnership instincts - you have shaped what gets built and how it ships</p></li><li><p>Track record of building accountable, high-ownership engineering organizations</p></li><li><p>Direct experience in one or more relevant domains: blockchain or crypto, fintech, payments, fraud or risk platforms, regulatory technology, or large-scale data platforms</p></li></ul>