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 for decentralized AI solutions, coordinating multi-stakeholder deployments across enterprise, government, and institutional environments. Serve as the primary client and partner contact, translate business requirements into AI deployment strategies using QVAC, and oversee roadmaps, milestones, dependencies, and production rollout. Partner with product, engineering, and research teams, manage governance and risk tracking, and deliver executive-level progress updates.

Location: Madrid

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Act as the primary point of contact for clients and partners during AI implementation initiatives, aligning expectations and execution.
•Guide clients in translating business requirements into AI deployment strategies using QVAC capabilities like 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 and limitations, and facilitate integration between client systems and QVAC components.
•Establish governance and reporting: implementation plans, risk tracking, decision logs, executive-level progress updates, and reusable documentation of architectures and learnings.

Key Requirements

•5+ years of experience in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments.
•Experience managing cross-functional implementations with multiple stakeholders, including clients and 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.

Experience:5+ yearsFintechAI/MLData infrastructureTechnical account managementDecentralized AI

Education:Bachelor's

Skills:CommunicationStakeholder managementGovernanceDocumentationManaging ambiguity

Languages:English

Tech Stack:QVACSDKUSDTKEETAPIsPythonBlockchainAI/MLEdge AIDistributed computePrivacy-preserving inference

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: Madrid

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Act as the primary point of contact for clients and partners during AI implementation initiatives, aligning expectations and execution.
•Guide clients in translating business requirements into AI deployment strategies using QVAC capabilities like 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 and limitations, and facilitate integration between client systems and QVAC components.
•Establish governance and reporting: implementation plans, risk tracking, decision logs, executive-level progress updates, and reusable documentation of architectures and learnings.

Key Requirements

•5+ years of experience in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments.
•Experience managing cross-functional implementations with multiple stakeholders, including clients and 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.

Experience:5+ yearsFintechAI/MLData infrastructureTechnical account managementDecentralized AI

Education:Bachelor's

Skills:CommunicationStakeholder managementGovernanceDocumentationManaging ambiguity

Languages:English

Tech Stack:QVACSDKUSDTKEETAPIsPythonBlockchainAI/MLEdge AIDistributed computePrivacy-preserving inference

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