Engagement Manager, AI Implementations

Role Overview

• 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.
• 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.
• 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.
• 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

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

Tech Stack

• Python

Benefits

• Health insurance
• Flexible work arrangements
• Professional development opportunities