Join our collaborative environment, where you'll help shape the future of AI and platform capabilities across Kinexys. Grow your skills, contribute to our AI strategy, and drive initiatives end-to-end while working alongside experienced product and technology partners. Don't miss this opportunity to be part of a dynamic team at the forefront of AI in digital assets.
As a Senior Associate in Kinexys AI and Platform Shared Services, you play a pivotal role in building and executing the AI strategy across Kinexys. You support the full lifecycle of AI initiatives — from discovery and data foundations through to delivery and adoption — while helping to establish the standards, governance, and operating model that will define how Kinexys builds with AI at scale. You are a strategic and technical thinker, equally comfortable with developers and senior stakeholders, with a genuine passion for AI and the drive to move fast across multiple priorities.
Job Responsibilities
- Supports the development and execution of the Kinexys AI strategy and roadmap, translating priorities into initiatives and tracking delivery against plan
- Manages end-to-end discovery and delivery of AI initiatives — from problem definition and requirements through to launch and adoption
- Contributes to the design and implementation of AI governance frameworks, including data standards, model oversight, and responsible AI practices
- Drives data management and standardisation efforts, ensuring data assets are well-governed and fit for AI and analytics use
- Collects and communicates metrics on initiative progress and platform performance to inform decision-making and senior stakeholder updates
- Partners with engineering and data teams to shape technical solutions, contributing requirements, user stories, and acceptance criteria
- Manages stakeholder relationships across product, technology, operations, and leadership — maintaining alignment across a matrixed organisation
- Contributes to platform shared services strategy, identifying opportunities to improve tooling, ways of working, and cross-team capabilities
- Monitors AI market trends, emerging tooling, and competitor activity to inform best practices and keep Kinexys ahead of the curve
- Supports internal AI enablement — helping teams across Kinexys understand and adopt AI capabilities effectively
Required Qualifications, Capabilities, and Skills
- Experience or equivalent expertise in product management, programme management, or a relevant domain with exposure to AI or data initiatives
- Developing knowledge of the AI and data product lifecycle, from discovery and data foundations through to production deployment
- Strong data literacy with exposure to data management, standardisation, or analytics workflows
- Technical fluency — able to engage with engineering and data teams, understand architectural tradeoffs, and contribute meaningfully to technical conversations
- Strong collaborator with proven ability to work alongside cross-functional partners including Technology, Operations, and Compliance
- Strategic thinker with the ability to connect the dots across business and functional areas to deliver high-impact solutions
- Highly organised with strong tracking and reporting discipline — comfortable owning metrics, dashboards, and stakeholder communications
- Comfortable working in a fast-paced environment with minimal guidance and a strong sense of ownership
- Genuine curiosity and enthusiasm for AI — you follow the space closely, form opinions, and bring energy to the work
Preferred Qualifications, Capabilities, and Skills
- Demonstrated prior experience working in a highly matrixed, complex organisation
- Hands-on experience building or contributing to enterprise AI or data platforms — from prototype to production at scale
- Familiarity with agentic AI frameworks, LLMs, RAG pipelines, or AI governance and evaluation tooling
- Experience in financial services, digital assets, payments, or a similarly regulated domain
- Prior exposure to distributed ledger technologies, tokenisation, or blockchain infrastructure
- Experience contributing to AI operating models, standards, or centre-of-excellence functions
