AI Engineering Lead

Tsai Center for Innovative Thinking at Yale (Tsai CITY)

AI Engineering Lead scaling reliable, explainable stakeholder intelligence for TSC’s enterprise risk products. Owning production AI architecture, evaluation, governance, data foundations and engineering teams.

Posted 8/12/2026full-timeHo Chi Minh City • 🇻🇳 VietnamSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI technical strategy, including the design and deployment of production AI systems, data management, and quality control. Proven ability to lead multidisciplinary teams and translate customer needs into actionable AI solutions.

Highest-signal resume keywords

AI Technical StrategyProduction AI SystemsData PipelinesLLM SystemsTeam Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningEntity ResolutionClassificationSummarisationExtractionEvaluationData TransformationRisk DetectionWorkflow AutomationIncident Response

Soft Skills

CommunicationMentoringProblem-SolvingCollaborationStakeholder Engagement

Tools & Technologies

GCPBigQueryAlloyDBVertex AICloud Data Platforms

Industry Keywords

Data ProtectionAuditabilityVendor RiskQuality ControlAI Workflows

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Own TSC's AI technical strategy across stakeholder mapping, classification, summarisation, entity resolution, risk detection, insight generation and workflow automation
Identify high-value AI opportunities based on customer problems, decision workflows and differentiated data assets
Partner with Product to translate customer needs into measurable requirements, acceptance criteria and release sequencing
Define technical approaches using deterministic software, machine learning, retrieval, LLMs, agents and human review
Own the lifecycle of material AI capabilities from data and evaluation design through deployment, monitoring, incident response and improvement
Build evaluation systems including golden datasets, regression tests, retrieval-quality checks, extraction and hallucination metrics, human-review thresholds and business KPIs
Define release-quality standards and governance for model and agent use, data protection, permissions, approvals and auditability
Establish incident, rollback and escalation processes for AI quality, security and operational failures
Own data foundations including ingestion, transformation, enrichment, entity resolution, labelling, retrieval, freshness, telemetry and feedback loops
Architect production AI systems and make decisions on agents, deterministic workflows and human review
Own AI unit economics across routing, caching, context windows, token usage, latency, fallbacks and vendor trade-offs
Establish repeatable agentic workflows with permissions, budgets, validation, stopping conditions and human approval gates
Hire, lead, mentor and grow AI Engineers and Data Engineers
Create operating practices for planning, documentation, code review, evaluation, quality gates, incident learning and architecture decisions
Partner with Product, Platform Engineering, Customer Success and company leadership
Support strategic customer and prospect conversations about AI architecture, quality controls, security, limitations and product direction

Requirements

What you’ll need

English proficiency
Typically 8+ years building production software, data or AI systems, including substantial experience leading multidisciplinary technical teams
Proven record of shipping and operating production AI or data systems, not only prototypes, demonstrations or research projects
Practical depth in LLM systems, retrieval-augmented generation, orchestration, embeddings, classification, summarisation, extraction and evaluation
Strong experience with data pipelines and cloud data platforms
Experience with GCP, BigQuery, AlloyDB, Vertex AI or comparable platforms preferred
Experience designing systems for enterprise or sensitive-data environments, including tenant isolation, access controls, auditability, vendor risk and secure model usage
Ability to review code, data models, system architecture and evaluation results in depth and contribute directly to technical problem-solving
Ability to explain AI strategy, architecture, quality, cost, risk and roadmap trade-offs to executives, customers and non-technical stakeholders
Experience designing evaluation, quality-control or regression systems for AI products
Experience building or governing agentic workflows with explicit permissions, stopping conditions, validation gates and human escalation
Experience managing model quality, cost and latency trade-offs in production
Experience turning ambiguous customer workflows into measurable, shippable AI features
Experience improving retrieval quality, entity resolution, classification or structured extraction over messy real-world datasets
Experience leading teams toward repeatable, observable and governed AI workflows
Experience supporting enterprise customer conversations involving AI reliability, security, architecture or limitations

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Tsai Center for Innovative Thinking at Yale (Tsai CITY) Website LinkedIn All Job Openings 51 - 200 employees Founded 2017 💼 Consulting 🏥 Healthcare 📣 Marketing Consulting
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Marketing Tsai Center for Innovative Thinking at Yale (Tsai CITY) is an initiative designed to inspire students from diverse backgrounds and disciplines to pursue innovative solutions for real-world problems. Tsai CITY offers a variety of programs, mentoring, and funding opportunities to support entrepreneurial endeavors, ranging from creative projects to nonprofit ventures. By connecting students with mentors and resources, Tsai CITY aims to cultivate the next wave of innovators and entrepreneurs at Yale University. AI Engineering Lead Job not on LinkedIn 🔥 1 minute ago 🏢🏡 Ho Chi Minh City – Hybrid ⏰ Full Time 🟠 Senior 🤖 AI Engineer BigQuery Cloud Google Cloud Platform Apply Now Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Own TSC's AI technical strategy across stakeholder mapping, classification, summarisation, entity resolution, risk detection, insight generation and workflow automation
Identify high-value AI opportunities based on customer problems, decision workflows and differentiated data assets
Partner with Product to translate customer needs into measurable requirements, acceptance criteria and release sequencing
Define technical approaches using deterministic software, machine learning, retrieval, LLMs, agents and human review
Own the lifecycle of material AI capabilities from data and evaluation design through deployment, monitoring, incident response and improvement
Build evaluation systems including golden datasets, regression tests, retrieval-quality checks, extraction and hallucination metrics, human-review thresholds and business KPIs
Define release-quality standards and governance for model and agent use, data protection, permissions, approvals and auditability
Establish incident, rollback and escalation processes for AI quality, security and operational failures
Own data foundations including ingestion, transformation, enrichment, entity resolution, labelling, retrieval, freshness, telemetry and feedback loops
Architect production AI systems and make decisions on agents, deterministic workflows and human review
Own AI unit economics across routing, caching, context windows, token usage, latency, fallbacks and vendor trade-offs
Establish repeatable agentic workflows with permissions, budgets, validation, stopping conditions and human approval gates
Hire, lead, mentor and grow AI Engineers and Data Engineers
Create operating practices for planning, documentation, code review, evaluation, quality gates, incident learning and architecture decisions
Partner with Product, Platform Engineering, Customer Success and company leadership
Support strategic customer and prospect conversations about AI architecture, quality controls, security, limitations and product direction 🎯 Requirements
English proficiency
Typically 8+ years building production software, data or AI systems, including substantial experience leading multidisciplinary technical teams
Proven record of shipping and operating production AI or data systems, not only prototypes, demonstrations or research projects
Practical depth in LLM systems, retrieval-augmented generation, orchestration, embeddings, classification, summarisation, extraction and evaluation
Strong experience with data pipelines and cloud data platforms
Experience with GCP, BigQuery, AlloyDB, Vertex AI or comparable platforms preferred
Experience designing systems for enterprise or sensitive-data environments, including tenant isolation, access controls, auditability, vendor risk and secure model usage
Ability to review code, data models, system architecture and evaluation results in depth and contribute directly to technical problem-solving
Ability to explain AI strategy, architecture, quality, cost, risk and roadmap trade-offs to executives, customers and non-technical stakeholders
Experience designing evaluation, quality-control or regression systems for AI products
Experience building or governing agentic workflows with explicit permissions, stopping conditions, validation gates and human escalation
Experience managing model quality, cost and latency trade-offs in production
Experience turning ambiguous customer workflows into measurable, shippable AI features
Experience improving retrieval quality, entity resolution, classification or structured extraction over messy real-world datasets
Experience leading teams toward repeatable, observable and governed AI workflows
Experience supporting enterprise customer conversations involving AI reliability, security, architecture or limitations Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Robotics AI Engineer 🕒 July 28 Menlo Research 11 - 50 🤖 Artificial Intelligence 🔧 Hardware 🏢 Enterprise Website LinkedIn All Job Openings Robotics AI Engineer working at Menlo Research to develop reinforcement learning policies for the Asimov robot. Collaborate closely with hardware teams and focus on real-world experiments. 🏢🏡 Ho Chi Minh City – Hybrid ⏰ Full Time 🟡 Mid-level 🟠 Senior 🤖 AI Engineer Python PyTorch Senior Frontend Engineer, AI-Assisted Development 🕒 July 27 Collaboration Betters The World TN 11 - 50 💼 Consulting 🤝 B2B Website LinkedIn All Job Openings Senior Frontend Engineer driving frontend architecture at CreditorWatch. Collaborating on the migration from Angular to React and championing AI-assisted workflows. 🏢🏡 Ho Chi Minh City – Hybrid ⏰ Full Time 🟠 Senior 🤖 AI Engineer Angular React Senior AI Engineer 🕒 April 4 CBTW 1001 - 5000 💼 Consulting 🏥 Healthcare 📦 Logistics Website LinkedIn All Job Openings Senior AI Engineer building and deploying AI/ML solutions for global tech consultancy in Ho Chi Minh City. Collaborating with teams to optimize AI systems with a focus on LLM and cloud technologies. 🏢🏡 Ho Chi Minh City – Hybrid ⏰ Full Time 🟠 Senior 🤖 AI Engineer Azure Cloud Python PyTorch Tensorflow Senior AI Engineer 🕒 April 3 CBTW 1001 - 5000 💼 Consulting 🏥 Healthcare 📦 Logistics Website LinkedIn All Job Openings Senior AI Engineer building and deploying AI/ML solutions in production for a consulting firm. Collaborating with engineering and product teams to deliver scalable AI systems and stay updated on AI advancements. 🏢🏡 Ho Chi Minh City – Hybrid ⏰ Full Time 🟠 Senior 🤖 AI Engineer Azure Cloud Python PyTorch Tensorflow Senior Frontend Engineer, AI-Assisted Development 🕒 March 18 CBTW 1001 - 5000 💼 Consulting 🏥 Healthcare 📦 Logistics Website LinkedIn All Job Openings Senior Frontend Engineer shaping the frontend architecture at a leading data and technology company. Collaborating with design and driving frontend quality across product groups. 🏢🏡 Ho Chi Minh City – Hybrid ⏰ Full Time 🟠 Senior 🤖 AI Engineer Angular React View More AI Engineer Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates About us Is Remote Rocketship legit? Privacy policy Terms of service Job board SEO course Remote Job Search MasterClass AI Apply Copilot OpenClaw job finder Find jobs using your resume Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs