OKX

Venture capital for blockchain startups

Vice President of AI Strategy & Transformation

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeHong KongNo salary listed

About the Job

Requirements

The candidate must have 10 or more years of experience in AI or deep learning, including at least 5 years in a senior leadership role at Director level or equivalent.
The candidate must have a demonstrated track record of shipping production AI systems that directly impacted business outcomes at scale, such as revenue, engagement, or efficiency.
The candidate must have deep expertise across the modern AI stack, including large language models, transformer architectures, retrieval-augmented generation, fine-tuning, reinforcement learning from human feedback or direct preference optimization, prompt engineering, and agentic AI frameworks.
The candidate must have a strong publication record, open-source contributions, or recognized AI thought leadership, such as conference talks, technical blog posts, courses, or widely adopted tools.
The candidate must be able to present complex technical concepts to board-level audiences and translate business needs into technical specifications.
The candidate must have an advanced degree (Master of Science or PhD) in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.

Responsibilities

Define and continuously refine the enterprise AI strategy, aligning it with revenue goals, product differentiation, and operational efficiency targets.
Conduct build-versus-buy-versus-partner analyses for foundation models, AI tooling, inference infrastructure, and data platforms.
Establish an AI governance framework covering model risk, data privacy, bias mitigation, and regulatory compliance across jurisdictions.
Serve as the primary AI advisor to the CEO and executive leadership team, translating frontier AI developments into actionable business implications.
Build and maintain a rolling 6-, 12-, and 24-month AI transformation roadmap with milestones, investment thresholds, and go/no-go decision points.
Identify and evaluate strategic AI acquisition, investment, and partnership opportunities.
Lead architecture and delivery of production-grade AI systems, including LLM-powered applications, retrieval-augmented generation systems, agentic workflows, fine-tuning pipelines, and prompt engineering frameworks at enterprise scale.
Design and implement AI-native infrastructure, including model serving, automated evaluation, A/B testing frameworks, prompt and model version control, and continuous quality and drift monitoring.
Build and optimize AI agent systems, multi-model orchestration, tool-use chains, and autonomous workflow engines to solve business problems end-to-end.
Build robust evaluation and benchmarking systems for AI outputs, measuring hallucination rates, task completion accuracy, latency, safety, and end-user satisfaction.
Personally prototype and review critical AI system designs, maintaining hands-on technical credibility with the engineering team.
Design and execute a company-wide AI literacy program tailored to executive leadership, product managers, engineers, operations, customer-facing teams, and support functions.
Create internal AI tooling, templates, and playbooks to enable business units to use AI capabilities, including prompt libraries, no-code/low-code AI interfaces, internal copilots, and AI-assisted workflows.
Establish an AI Center of Excellence as a hub for best practices, reusable components, and cross-functional AI project incubation.
Implement a structured AI use-case intake and prioritization process, partnering with business units to identify high-ROI opportunities, scope them, and execute with embedded AI support.
Build an AI talent strategy by defining hiring profiles for AI engineers and applied AI roles, designing technical interview processes, and developing retention programs for AI talent.
Foster responsible AI experimentation through psychological safety, rapid experimentation, rigorous post-mortems, and knowledge sharing across business units.

Desired Qualifications

Experience in fintech, crypto/blockchain, or regulated industries with complex compliance requirements.
Hands-on experience building AI-native products in consumer-facing, high-throughput environments with millions of daily active users.
A track record of driving company-wide AI adoption initiatives and organization-wide cultural and process transformation.
Experience building or contributing to open-source AI tools, frameworks, or educational content adopted by the broader community.
Familiarity with AI regulatory landscapes across multiple jurisdictions, including the United States, the EU AI Act, and APAC frameworks.
Published authorship or recognition as an AI educator, such as books, widely read technical blogs, MOOCs, or workshops.

Who We Are

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.

OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.

Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.

About the Opportunity

We are seeking a VP of AI Strategy & Transformation — a hands-on technical leader who combines deep AI expertise with the strategic vision and executive influence to drive AI adoption across every business unit. This is not a research role or a traditional engineering management position. We need someone who has personally built and shipped production AI systems, understands the frontier of foundation models and agentic AI, and can translate that expertise into company-wide transformation.

The ideal candidate is, first and foremost, a deeply technical AI practitioner — someone who has architected and deployed AI systems at scale, and who can channel that credibility into driving AI adoption across every function of the organization. Not a theorist, not a people-manager-only — a builder-leader who ships and who makes others ship.

What You’ll Be Doing

1. Company AI Strategy & Transformation

Own the company’s AI roadmap end-to-end — from foundation model selection to business-unit-specific deployment plans:

Define and continuously refine the enterprise AI strategy, aligning it to revenue goals, product differentiation, and operational efficiency targets.
Conduct rigorous build-vs-buy-vs-partner analysis for foundation models, AI tooling, inference infrastructure, and data platforms.
Establish an AI governance framework covering model risk, data privacy, bias mitigation, and regulatory compliance across jurisdictions.
Serve as the primary AI advisor to the CEO and executive leadership team; translate frontier AI developments into actionable business implications.
Build and maintain a rolling 6/12/24-month AI transformation roadmap with clear milestones, investment thresholds, and go/no-go decision points.
Identify and evaluate strategic AI acquisition, investment, and partnership opportunities.

2. System Building & Technical Execution

Architect and deliver production-grade AI systems that create measurable business impact — not just prototypes:

Lead the architecture of LLM-powered applications including RAG systems, agentic workflows, fine-tuning pipelines, and prompt engineering frameworks at enterprise scale.
Design and implement AI-native infrastructure: model serving, automated evaluation, A/B testing frameworks, version control for prompts and models, and continuous monitoring for quality and drift.
Build and optimize AI agent systems, multi-model orchestration, tool-use chains, and autonomous workflow engines that solve real business problems end-to-end.
Build robust evaluation and benchmarking systems for AI outputs — measuring hallucination rates, task completion accuracy, latency, safety, and end-user satisfaction.
Personally prototype and review critical AI system designs; maintain hands-on technical credibility with the engineering team.

3. Organizational AI Enablement & Adoption

Drive AI adoption across every business unit — making AI a core competency for the entire organization, not just the engineering team:

Design and execute a company-wide AI literacy program segmented by role: executive leadership, product managers, engineers, operations, customer-facing teams, and support functions.
Create internal AI tooling, templates, and playbooks that make it radically easy for every business unit to leverage AI capabilities (prompt libraries, no-code/low-code AI interfaces, internal copilots, AI-assisted workflows).
Establish an AI Center of Excellence that serves as the hub for best practices, reusable components, and cross-functional AI project incubation.
Implement a structured AI use-case intake and prioritization process: partner with each business unit to identify high-ROI AI opportunities, scope them properly, and execute with embedded AI support.
Build an AI talent strategy: define hiring profiles for AI engineers and applied AI roles, design technical interview processes, and develop retention programs for top AI talent.
Foster a culture of responsible AI experimentation: psychological safety to try and fail fast, coupled with rigorous post-mortems and knowledge sharing across BUs.

What We Look For In You

10+ years in AI / deep learning, with at least 5 years in a senior leadership role (Director+ or equivalent at a top-tier tech company, high-growth startup, or leading AI lab).
Demonstrated track record of shipping production AI systems that directly impacted business outcomes at scale (revenue, engagement, efficiency).
Deep expertise across the modern AI stack: large language models, transformer architectures, RAG, fine-tuning, RLHF/DPO, prompt engineering, and agentic AI frameworks.
Strong publication record, open-source contributions, or recognized thought leadership in the AI community (conference talks, technical blog posts, courses, or widely-adopted tools).
Exceptional communication skills: ability to present complex technical concepts to board-level audiences and translate business needs into technical specifications.
Advanced degree (MS or PhD) in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.

Nice to Haves

Experience in fintech, crypto/blockchain, or regulated industries with complex compliance requirements.
Hands-on experience building AI-native products in consumer-facing, high-throughput environments (millions of daily active users).
Track record of driving company-wide AI adoption initiatives — not just team-level, but organization-wide cultural and process transformation.
Experience building or contributing to open-source AI tools, frameworks, or educational content adopted by the broader community.
Familiarity with AI regulatory landscapes across multiple jurisdictions (US, EU AI Act, APAC frameworks).
Published author or recognized educator in AI (books, widely-read technical blogs, MOOCs, or workshops).

Perks & Benefits

Competitive total compensation package
L&D programs and Education subsidy for employees' growth and development
Various team building programs and company events
Wellness and meal allowances
Comprehensive healthcare schemes for employees and dependants
More that we love to tell you along the process!

OKX Statement:

OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status.

#LI-VW1 #ONSITE

Notice:

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About the Company

OKX

Venture capital for blockchain startups

OKX Ventures acts as the investment arm of the OKX cryptocurrency exchange, funding and supporting blockchain, DeFi, and Web3 projects. It invests across a wide range of areas—from infrastructure and middleware to applications and games—aiming to strengthen the crypto ecosystem. The firm provides capital and access to OKX’s network of partners and advisors to help portfolio companies grow and succeed. Notable holdings include Polygon, Solana, and Avalanche, reflecting a strategy focused on projects with potential to impact the crypto industry at large. OKX Ventures differentiates itself through its crypto-native perspective, extensive industry network, and active involvement in portfolio development, rather than just providing funding. Its goal is to identify promising projects and help them scale, contributing to a more robust and innovative blockchain ecosystem.

Company size: 5,001-10,000
Company stage: Not listed
Total funding: $1.1B
Headquarters: Singapore, Singapore
Founded: 2017

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