Engagement Manager, AI Implementations

About the role

This role involves leading the implementation of AI solutions, specifically those leveraging QVAC capabilities like local inference and privacy-preserving architectures. The Engagement Manager will serve as the main contact for clients and partners, guiding them through the process of translating business needs into AI deployment strategies. Success in this position means ensuring clear communication, aligning expectations, and executing projects efficiently from initial planning through to production.

The manager will oversee the entire implementation lifecycle, defining roadmaps and milestones for AI models, infrastructure, and integration. This includes tracking progress across multiple concurrent AI deployments and ensuring timely delivery. A key aspect is aligning client expectations with the product's actual capabilities, preventing scope creep, and ensuring solutions are ready for production environments.

Cross-functional collaboration is central to this role, requiring coordination with product, engineering, and research teams to align on QVAC capabilities and roadmap. The manager will also facilitate integration between client systems and QVAC components, working with legal and compliance teams when necessary for sensitive AI deployments. Establishing governance frameworks, tracking risks, and producing executive-level updates are also core responsibilities.

The competitive salary for this position ranges from $100,000 to $500,000 per year.

Skills that matter here

• program management: This role requires 5+ years of experience in program management to lead AI implementation initiatives from start to finish.
• technical account management: Experience in technical account management is relevant for acting as the primary point of contact for clients and partners during AI implementations.
• AI/ML deployment concepts: Familiarity with AI/ML deployment concepts, such as model inference and distributed compute architectures, is necessary to guide clients and coordinate technical aspects.
• APIs, SDK integrations: Understanding APIs and SDK integrations is important for facilitating the connection between client systems and QVAC components.
• stakeholder management: Strong stakeholder management skills are crucial for maintaining structured communication flows with internal teams, clients, and external partners.
• decentralized technologies, blockchain: Experience with decentralized technologies or blockchain is a plus, given Tether's focus on digital finance and pioneering a global financial revolution.

Who this role suits

• A person with a strong background in managing complex technical projects, particularly those involving AI or data infrastructure.
• Someone who can effectively bridge the gap between technical details and business requirements, communicating clearly with both engineers and clients.
• An individual who thrives in dynamic, early-stage environments and can manage ambiguity while maintaining a structured approach to project governance.
• A professional adept at coordinating across multiple internal and external teams, ensuring alignment and timely delivery of solutions.

From the employer

Responsibilities

• Client & Partner Engagement

Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution.

Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures).

Support Expansion team in shaping AI-related opportunities by providing input on feasibility, integration complexity, and delivery approach.

Identify opportunities to extend implementations across additional use cases, geographies, or Tether technologies.

• Implementations Oversight

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.

Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning.

Track progress across multiple concurrent AI deployments, ensuring timely delivery and readiness for production environments.

• Cross-functional Coordination

Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution.

Facilitate integration between client systems and QVAC components, including model deployment pipelines, APIs, and compute environments.

Work with legal and compliance teams where required, particularly in sensitive AI deployments involving data locality or privacy constraints.

Maintain structured communication flows across all stakeholders involved in the implementation lifecycle.

• Governance & Reporting

Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs.

Produce executive-level updates summarizing progress, risks, blockers, and next steps.

Ensure documentation of implementation architectures, deployment patterns, and key learnings for reuse across future projects.

Support escalation management and ensure timely resolution of technical or operational challenges.

Requirements

• Core Experience

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.

• Technical Understanding

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.

Ability to engage in technical discussions with engineering teams while maintaining business-level clarity with clients.

• Communication & Execution

Strong communication and stakeholder management skills, including experience working with enterprise or government entities.

Structured approach to project tracking, documentation, and governance.

Ability to manage ambiguity and operate in fast-evolving, early-stage environments.

• 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).

Conditions

• Competitive salary ranging from $100,000 to $500,000 per year.
• Opportunity to work remotely with a global team.
• Engage in innovative projects at the forefront of digital finance.