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About the role
Key responsibilities & impact- 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
What you’ll need- 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.
- Structured approach to project tracking, documentation, and governance.
- Ability to manage ambiguity and operate in fast-evolving, early-stage environments.
Benefits
Comp & perks- Flexible working arrangements
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI implementationAI deployment strategiesmodel inferencedistributed compute architecturesAPIsSDK integrationssystem architecture patternsproject trackingdocumentationgovernance frameworks
Soft Skills
communicationstakeholder managementcross-functional collaborationstructured executionrisk trackingdecision makingambiguity managementoperational problem solvingexpectation alignmentexecutive-level reporting