Engagement Manager – AI Implementations

📋 Description

• Serve as the main liaison for clients and partners during AI implementation projects, ensuring effective communication, alignment of expectations, and organized execution.

• Assist clients in converting business requirements into AI deployment strategies utilizing QVAC capabilities (local inference, delegated computing, privacy-preserving architectures).

• Aid the Expansion team in identifying AI-related opportunities by offering insights on feasibility, integration challenges, and delivery methodologies.

• Discover chances to broaden implementations across additional use cases, regions, or Tether technologies.

• Oversee the complete coordination of QVAC-based implementations from project initiation to production deployment.

• Establish implementation roadmaps, key milestones, and dependencies concerning AI models, infrastructure, and integration layers.

• Ensure alignment between client expectations and the actual capabilities of the product, preventing scope creep or misrepresentation.

• Monitor progress across multiple simultaneous AI deployments to guarantee timely delivery and readiness for production settings.

• Collaborate closely with product, engineering, and research teams to synchronize on QVAC capabilities, limitations, and roadmap advancements.

• Facilitate the integration of client systems with QVAC components, including model deployment pipelines, APIs, and computing environments.

• Partner with legal and compliance teams as necessary, especially in sensitive AI deployments that involve data locality or privacy considerations.

• Sustain structured communication channels among all stakeholders engaged in the implementation process.

• Create and maintain governance frameworks that include implementation plans, risk management, and decision logs.

• Generate executive-level updates that summarize progress, risks, challenges, and subsequent steps.

• Ensure the documentation of implementation architectures, deployment patterns, and key insights for future project reuse.

• Assist in managing escalations and ensure the prompt resolution of technical or operational issues.

⛳️ Requirements

• Over 5 years of experience in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology settings.

• Demonstrated experience in managing cross-functional implementations involving various stakeholders (internal teams, clients, external partners).

• Strong capability to operate at the intersection of technical and business disciplines.

• Familiarity with AI/ML deployment concepts, including model inference, edge/local AI, and distributed computing architectures.

• Understanding of APIs, SDK integrations, and system architecture patterns.

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

• Excellent communication and stakeholder management skills, including experience working with enterprise or government organizations.

• Structured approach to project tracking, documentation, and governance.

• Capacity to manage uncertainty and operate in rapidly changing, early-stage environments.

• Experience with decentralized technologies, blockchain, or privacy-preserving systems (Nice to Have).

• Exposure to AI infrastructure tools or MLOps workflows (Nice to Have).

• Experience in regulated industries or public sector projects (Nice to Have).

• Basic knowledge of programming or scripting environments (Python, APIs, CLI tools) (Nice to Have).

🏝️ Benefits

• Flexible work arrangements

• Professional development opportunities