Engagement Manager, AI Implementations

Stack

Responsibilities

• ▹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 using QVAC (local inference, delegated compute, privacy-preserving architectures)
• ▹Support the Expansion team in shaping AI opportunities with input on feasibility, integration complexity and delivery approach
• ▹Identify opportunities to extend implementations across additional use cases, geographies or Tether technologies
• ▹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
• ▹Align client expectations with actual product capabilities, avoiding scope drift
• ▹Track progress across multiple concurrent AI deployments
• ▹Coordinate closely with product, engineering and research teams
• ▹Facilitate integration between client systems and QVAC components, including model deployment pipelines, APIs and compute environments
• ▹Work with legal and compliance teams on sensitive deployments involving data locality or privacy constraints
• ▹Establish and maintain governance frameworks including implementation plans, risk tracking and decision logs
• ▹Produce executive-level updates on progress, risks, blockers and next steps
• ▹Document implementation architectures and deployment patterns for reuse
• ▹Support escalation management and timely resolution of technical or operational challenges

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 with multiple stakeholders (internal teams, clients, external partners)
• ▹Ability to operate at the intersection of technical and business domains
• ▹Familiarity with AI/ML deployment concepts: model inference, edge/local AI, distributed compute architectures
• ▹Understanding of APIs, SDK integrations and system architecture patterns
• ▹Ability to engage in technical discussions with engineering teams while keeping business-level clarity with clients
• ▹Strong communication and stakeholder management skills, including experience with enterprise or government entities
• ▹Structured approach to project tracking, documentation and governance
• ▹Ability to manage ambiguity in fast-evolving, early-stage environments
• ▹Excellent English communication skills

Nice to have

• ▹Experience with decentralized technologies, blockchain or privacy-preserving systems
• ▹Exposure to AI infrastructure tooling or MLOps workflows
• ▹Experience in regulated industries or public sector projects
• ▹Basic familiarity with programming or scripting environments (Python, APIs, CLI tools)

Soft skills

What we offer

• ▹Global team working remotely from around the world

About the company

Tether is the company behind the USDT stablecoin and digital asset tokenization services; its business areas include Tether Finance, Power, Data, Education and Evolution.