Global Head of Analytics and AI Platform Engineering, Managing Director
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- Hangzhou, Zhejiang
- Permanent
- Full-time
- Support SSIM’s Analytics and AI vision and strategy; lead end‑to‑end implementation of platform infrastructure, software application, foundational data science capabilities, advanced analytics and AI frameworks, tooling, ML/LLM Ops, and Model Observability.
- Lead and mentor high‑performing engineering teams across the US, China, India, and Poland—building a culture grounded in deep technology expertise and accountability (not traditional staff‑augmentation models).
- Define SSIM’s Analytics and AI Platform architecture, establish engineering standards, and guide implementation and governance practices.
- Ensure a modular, scalable, and reusable architecture to eliminate siloed development and accelerate time to market.
- Champion engineering excellence, technical rigor, and innovation across the organization.
- Innovation & Best Practices: Evaluate, adopt, and standardize cutting‑edge technology capabilities—including IAC, Cloud Computing/Agnostic, GPU/TPU/FPGA/CUDA, AI frameworks, GenAI/Agentic AI integration protocols/frameworks, distributed computing, and HADR.
- Quality & Performance: Ensure solutions meet the highest engineering standards through code reviews, testing frameworks, and adherence to industry guidelines.
- Collaboration & Mentorship: Build a collaborative engineering community focused on continuous learning, knowledge sharing, and professional development.
- Scalability & Resilience: Architect systems capable of supporting global business workloads with strong reliability and performance characteristics.
- Security & Compliance: Uphold stringent risk, security, and regulatory requirements; ensure robust data protection and governance.
- Lead global analytics and AI platform engineering teams with a focus on innovation, delivery excellence, and operating leverage.
- Manage major vendor relationships—including analytics and AI platform providers and service partners—ensuring strong integration, service quality, and contractual outcomes.
- Oversee the full analytics and AI business capability deployment required environment from sandbox, development, QA/UAT, production, to disaster recovery across a diverse set of use cases and global users
- Master’s degree required (Computer Science, Electrical Engineering or related field)
- 15+ years in core engineering role at large enterprise ideally asset management industry.
- 15+ years hands‑on engineering experience with a strong track record delivering analytics and/or AI solutions and platforms.
- Proven experience leading global technology organizations across infrastructure, IAC, ML/LLM Ops, analytics and AI frameworks/tools, FinOps, high availability and disaster recovery, with strong delivery execution.
- Strong understanding of the analytics and AI vendor landscape and demonstrated experience adopting vendor products and open‑source frameworks to improve scale and growth.
- Exceptional leadership, stakeholder management, communication, and relationship‑building skills.
- Fluent in English; highly detail‑oriented, results‑driven, candid, and execution‑focused.
- Prior AI platform engineering leadership experience in large financial institution.
- CFA Level I or equivalent credential.