
Vice President, AI Strategy & Transformation
at OKX
Posted 13 hours ago
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**Vice President, AI Strategy & Transformation:** Lead AI innovation, driving strategy and execution for a growing tech company. Key responsibilities involve defining AI vision, developing roadmaps, and managing teams. Required skills include demonstrated success in AI leadership roles, proficiency in modern AI tools and frameworks, and excellent stakeholder management. This is a senior role demanding 10+ years of relevant experience. Collaborate with cross-functional teams to ensure AI strategies align with overall business objectives, while constantly monitoring AI landscape for trends and opportunities.
Who We Are
About the Opportunity
What You’ll Be Doing
1. Company AI Strategy & Transformation
- 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
- 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
- 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!
