VP of Engineering
New
United StatesFull-TimeVp
Salary not disclosed
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Job Details
- Experience
- 10+ years of engineering experience, including 5+ years in senior leadership roles
- Required Skills
- Artificial IntelligenceBlockchainSaaSDistributed Systems
Requirements
- 10+ years of engineering experience, including 5+ years in senior leadership roles such as VP Engineering or Head of Engineering.
- Proven experience leading large-scale platform migrations or system rebuilds without customer disruption.
- Strong background in distributed systems, low-latency architectures, and high-availability SaaS platforms.
- Hands-on experience operating in data-intensive environments, ideally including multi-tenant or multi-chain systems.
- Demonstrated ability to integrate AI and automation into engineering workflows to improve productivity and delivery speed.
- Strong product and business acumen with the ability to influence roadmap and technical direction.
- Proven track record of building high-accountability, high-performance engineering organizations.
- Experience in blockchain, fintech, payments, fraud/risk systems, regtech, or large-scale data platforms is highly preferred.
- Excellent leadership, communication, and stakeholder management skills in executive environments.
Responsibilities
- Own and drive the end-to-end migration from legacy systems to a new AI-native data pipeline across all core products and services.
- Ensure seamless platform transition with no SLA regressions, no service interruptions, and full preservation of customer trust.
- Lead architectural design decisions across data models, service cutovers, parallel runs, and system integration strategies.
- Restore and enhance platform performance, scalability, and reliability, including improvements in latency, throughput, and stability.
- Oversee engineering execution across multi-chain and distributed systems supporting high-volume SaaS workloads.
- Rebuild engineering management structures, defining clear accountability, delivery standards, and organizational effectiveness.
- Drive adoption of AI-powered engineering tools and automation to improve productivity, testing, and deployment velocity.
- Partner with product, GTM, customer success, and finance teams to align engineering execution with business outcomes.
- Own engineering budget planning, hiring strategy, vendor selection, and operational efficiency improvements.
- Communicate progress, risks, and trade-offs clearly to executive leadership and board stakeholders.
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