Engagement Manager, AI Implementations

🕒 May 15

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Tether.to

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

₿ Crypto

💳 Fintech

💸 Finance

Crypto • Fintech • Finance

Tether. to is a leading digital asset company that pioneers the use of stablecoins in the blockchain space. As the most widely adopted stablecoin, Tether tokens are designed to be pegged 1-to-1 with fiat currencies, offering a stable digital asset option for users. The platform facilitates these token transactions across multiple blockchains, enhancing cross-border transactions while maintaining transparency with daily records of total assets and reserves. Tether's initiatives include educational programs promoting digital asset usage, especially targeting regions like the Middle East, Turkey, and the Philippines. Tether thus positions itself as a disruptor in the traditional financial system by enabling a stable, efficient method of handling transactions in the digital currency world.

📋 Description

• Act as the primary point of contact for clients and partners during AI implementation initiatives. • Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities. • Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment. • Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers. • Coordinate closely with product, engineering, and research teams to align on QVAC capabilities. • Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs.

🎯 Requirements

• 5+ years of experience in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments. • Proven experience managing cross-functional implementations involving multiple stakeholders (internal teams, clients, external partners). • Strong ability to operate at the intersection of technical and business domains. • Familiarity with AI/ML deployment concepts, including model inference, edge/local AI, and distributed compute architectures. • Understanding of APIs, SDK integrations, and system architecture patterns. • Strong communication and stakeholder management skills, including experience working with enterprise or government entities. • Ability to manage ambiguity and operate in fast-evolving, early-stage environments.

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities