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 the implementation of AI-driven initiatives powered by QVAC, coordinating decentralized AI deployments across enterprise, government, and institutional environments. Act as the primary point of contact for clients and partners, translating business requirements into deployment strategies while aligning expectations with product capabilities. Own end-to-end coordination from kickoff through production rollout, define roadmaps and dependencies, and work with product, engineering, research, and legal/compliance stakeholders to ensure successful delivery.

Location: London

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Serve as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication and structured execution
•Translate business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures)
•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
•Coordinate with product, engineering, research, and legal/compliance teams; facilitate integration between client systems and QVAC components, and provide executive-level reporting

Key Requirements

•5+ years in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments
•Experience managing cross-functional implementations with internal teams, clients, and external partners
•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 with enterprise or government entities

Experience:AIData infrastructureComplex technologyDecentralized technology

Education:Bachelor's

Skills:CommunicationStakeholder managementProject trackingGovernanceManaging ambiguity

Languages:English

Tech Stack:QVACSDKAI/MLModel inferenceEdge/local AIDistributed computeAPIsPythonCLI toolsBlockchainsMLOpsPrivacy-preserving inferenceDelegated inferenceLocal 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: London

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Serve as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication and structured execution
•Translate business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures)
•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
•Coordinate with product, engineering, research, and legal/compliance teams; facilitate integration between client systems and QVAC components, and provide executive-level reporting

Key Requirements

•5+ years in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments
•Experience managing cross-functional implementations with internal teams, clients, and external partners
•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 with enterprise or government entities

Experience:AIData infrastructureComplex technologyDecentralized technology

Education:Bachelor's

Skills:CommunicationStakeholder managementProject trackingGovernanceManaging ambiguity

Languages:English

Tech Stack:QVACSDKAI/MLModel inferenceEdge/local AIDistributed computeAPIsPythonCLI toolsBlockchainsMLOpsPrivacy-preserving inferenceDelegated inferenceLocal 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