Tether.io

3 days ago

Engagement Manager, AI Implementations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Lead end-to-end implementation of AI-driven initiatives using QVAC, Tether’s SDK for local AI and delegated inference. Own multi-stakeholder deployments across enterprise, government, and institutional environments—translating business requirements into deployment strategies, coordinating engineering/product/research teams, and tracking roadmaps, milestones, risks, and production readiness. Ensure clear stakeholder alignment, prevent scope drift, and produce executive updates and reusable implementation documentation.

Location: Paris

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Act as primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication and expectation alignment.
•Guide clients in converting business requirements into AI deployment strategies using QVAC capabilities, including local inference and privacy-preserving architectures.
•Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment, defining roadmaps, milestones, and dependencies.
•Coordinate with product, engineering, and research teams to align on QVAC capabilities/limitations and facilitate integration between client systems and QVAC components.
•Establish governance and reporting: track risks and progress across concurrent deployments, provide executive updates, and document architectures and learnings for reuse.

Key Requirements

•5+ years of experience in program management, technical account management, or delivery roles in AI, data infrastructure, or complex technology environments.
•Manage cross-functional implementations across multiple stakeholders, including clients and external partners.
•Translate business requirements into AI deployment strategies and participate in technical discussions while staying clear at the client level.
•Familiarity with AI/ML deployment concepts such as model inference, edge/local AI, and distributed compute architectures.
•Understanding of APIs, SDK integrations, and system architecture patterns; ability to operate with ambiguity in fast-evolving environments.

Experience:5+ yearsAIData infrastructureComplex technology environments

Education:Bachelor's

Skills:CommunicationStakeholder managementStructured executionDocumentationRisk tracking

Languages:English

Tech Stack:QVACSDKAIMLEdge AILocal inferenceDelegated inferencePrivacy-preserving architecturesAPIsModel deployment pipelinesDistributed computeMLOpsBlockchainPythonCLI toolsUSDTKEET

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website

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Tether.io

3 days ago

Engagement Manager, AI Implementations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Location: Paris

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Act as primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication and expectation alignment.
•Guide clients in converting business requirements into AI deployment strategies using QVAC capabilities, including local inference and privacy-preserving architectures.
•Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment, defining roadmaps, milestones, and dependencies.
•Coordinate with product, engineering, and research teams to align on QVAC capabilities/limitations and facilitate integration between client systems and QVAC components.
•Establish governance and reporting: track risks and progress across concurrent deployments, provide executive updates, and document architectures and learnings for reuse.

Key Requirements

•5+ years of experience in program management, technical account management, or delivery roles in AI, data infrastructure, or complex technology environments.
•Manage cross-functional implementations across multiple stakeholders, including clients and external partners.
•Translate business requirements into AI deployment strategies and participate in technical discussions while staying clear at the client level.
•Familiarity with AI/ML deployment concepts such as model inference, edge/local AI, and distributed compute architectures.
•Understanding of APIs, SDK integrations, and system architecture patterns; ability to operate with ambiguity in fast-evolving environments.

Experience:5+ yearsAIData infrastructureComplex technology environments

Education:Bachelor's

Skills:CommunicationStakeholder managementStructured executionDocumentationRisk tracking

Languages:English

Tech Stack:QVACSDKAIMLEdge AILocal inferenceDelegated inferencePrivacy-preserving architecturesAPIsModel deployment pipelinesDistributed computeMLOpsBlockchainPythonCLI toolsUSDTKEET

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website