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 implementations of AI-driven initiatives powered by QVAC, orchestrating multi-stakeholder deployments across enterprise, government, and institutional environments. Serve as the primary client and partner contact, translate requirements into deployment strategies, define roadmaps and milestones, and coordinate product, engineering, research, and compliance teams. Drive onboarding through production rollout while maintaining governance, risk tracking, and executive reporting for concurrent AI use cases.

Location: Bucharest

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication and expectation alignment.
•Guide clients in translating business requirements into AI deployment strategies using QVAC capabilities (local inference, delegated compute, privacy-preserving architectures).
•Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment, including defining roadmaps, milestones, and dependencies.
•Coordinate with product, engineering, and research teams to align on QVAC capabilities and roadmap evolution, and facilitate integration between client systems and QVAC components.
•Establish governance and reporting, including implementation plans, risk tracking, decision logs, executive updates, documentation, and escalation management.

Key Requirements

•5+ years in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments.
•Proven experience managing cross-functional implementations with multiple stakeholders (internal teams, clients, 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 technology environments

Education:Bachelor's

Skills:CommunicationStakeholder managementGovernanceDocumentationManaging ambiguity

Languages:English

Tech Stack:QVACSDKAIMLModel inferenceEdge/local AIDistributed compute architecturesAPIsBlockchainPrivacy-preserving architecturesMLOpsPythonCLI tools

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: Bucharest

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication and expectation alignment.
•Guide clients in translating business requirements into AI deployment strategies using QVAC capabilities (local inference, delegated compute, privacy-preserving architectures).
•Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment, including defining roadmaps, milestones, and dependencies.
•Coordinate with product, engineering, and research teams to align on QVAC capabilities and roadmap evolution, and facilitate integration between client systems and QVAC components.
•Establish governance and reporting, including implementation plans, risk tracking, decision logs, executive updates, documentation, and escalation management.

Key Requirements

•5+ years in program management, technical account management, or delivery roles within AI, data infrastructure, or complex technology environments.
•Proven experience managing cross-functional implementations with multiple stakeholders (internal teams, clients, 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 technology environments

Education:Bachelor's

Skills:CommunicationStakeholder managementGovernanceDocumentationManaging ambiguity

Languages:English

Tech Stack:QVACSDKAIMLModel inferenceEdge/local AIDistributed compute architecturesAPIsBlockchainPrivacy-preserving architecturesMLOpsPythonCLI tools

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