Salary: £62,000 - 102,000 per year
Requirements
- Formal training or certification on software engineering concepts and 5+ years of applied experience
- Advanced proficiency in Python and infrastructure-as-code, with modern software engineering practices
- Deep hands-on experience with Kubernetes, containerisation, and cloud-native deployment patterns
- Strong CI/CD experience and a track record of building deployment and release automation
- Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps)
- Practical experience with observability tooling (metrics, logging, tracing) and production incident response
- Experience operating ML/LLM workloads in production (LLMOps, inference reliability, cost/performance management)
- Strong communication skills and the ability to set standards other engineers adopt
- Industry-recognised container/Kubernetes certification (e.g., CKAD or similar)
- Masters degree in Computer Science, Engineering, or a related technical field, or equivalent applied experience
- SRE experience and familiarity with reliability practices (SLOs, error budgets) is preferred
- Experience within financial services technology is preferred
- Familiarity with JPM-internal platform, cloud, and AI/ML infrastructure is preferred for internal candidates
Responsibilities
- Design and build our platform, including deployment pipelines, model serving, containerisation, orchestration, and environment management
- Set the standard for reliability, observability, and operational excellence across our production AI/ML services
- Build tooling and paved paths that help AI engineers ship agentic AI and ML products safely and quickly
- Implement platform-level security, secrets management, and access controls to firm-wide standards
- Partner with data and AI engineers to productionise models and coordinate with external infrastructure functions to reduce operational dependency and risk
- Lead capacity, cost, and performance management for our compute and inference workloads
- Mentor platform and DevOps engineers and set engineering standards through design and code review
- Champion our culture of diversity, opportunity, inclusion, and respect
Technologies
- Agentic AI
- AI
- CI/CD
- Cloud
- DevOps
- Kubernetes
- LLM
- Machine Learning
- MLOps
- Model Serving
- Python
- Security
- Network
More
We are J.P. Morgan Chase, a global leader in financial services, serving prominent corporations, governments, wealthy individuals, and institutional investors. Our International Private Bank Technology Artificial Intelligence and Machine Learning team is hiring a Senior VP Platform Engineer to help design and own the platform, tooling, and infrastructure behind our agentic AI and machine learning products. This is a full-time role based within our Asset & Wealth Management business. We offer a first-class business in a first-class way approach, value long-term client partnerships, and are committed to diversity, inclusion, and equal opportunity, with reasonable accommodations available where needed.
last updated 36 week of 2026
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