Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Join our collaborative environment at JPMorganChase, where you'll help shape the future of AI and platform capabilities across Kinexys. As a Senior Associate in Kinexys AI and Platform Shared Services, you will play a pivotal role in building and executing the AI strategy across Kinexys. You will 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. Working alongside experienced product and technology partners, you will contribute to driving initiatives end-to-end and be part of a dynamic team at the forefront of AI in digital assets. This role requires a strategic and technical thinker who is equally comfortable engaging with developers and senior stakeholders, with a genuine passion for AI and the ability to manage multiple priorities effectively.

Key Responsibilities
- Support the development and execution of the Kinexys AI strategy and roadmap, translating priorities into initiatives and tracking delivery against plan
- Manage end-to-end discovery and delivery of AI initiatives, from problem definition and requirements through to launch and adoption
- Contribute to the design and implementation of AI governance frameworks, including data standards, model oversight, and responsible AI practices
- Drive data management and standardisation efforts, ensuring data assets are well-governed and fit for AI and analytics use
- Collect and communicate metrics on initiative progress and platform performance to inform decision-making and senior stakeholder updates
- Partner with engineering and data teams to shape technical solutions, contributing requirements, user stories, and acceptance criteria
- Manage stakeholder relationships across product, technology, operations, and leadership, maintaining alignment across a matrixed organisation
- Contribute to platform shared services strategy, identifying opportunities to improve tooling, ways of working, and cross-team capabilities
- Monitor AI market trends, emerging tooling, and competitor activity to inform best practices and keep Kinexys ahead of the curve
- Support internal AI enablement, helping teams across Kinexys understand and adopt AI capabilities effectively

Experience
- 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 to engage with engineering and data teams, understand architectural tradeoffs, and contribute meaningfully to technical conversations
- Proven ability to collaborate with cross-functional partners including Technology, Operations, and Compliance
- Comfortable working in a fast-paced environment with minimal guidance and a strong sense of ownership

About You
- 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
- Genuine curiosity and enthusiasm for AI, following the space closely, forming opinions, and bringing energy to the work

Preferred Qualifications
- 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, large language models (LLMs), retrieval-augmented generation (RAG) pipelines, or AI governance and evaluation tooling
- Experience in financial services, digital assets, payments, or similarly regulated domains
- Prior exposure to distributed ledger technologies, tokenisation, or blockchain infrastructure
- Experience contributing to AI operating models, standards, or centre-of-excellence functions