About this role
Salary: £100,000 - 100,000 per year
Requirements: Formal training or certification on software engineering concepts and 5 years applied experienceAdvanced proficiency in Python and infrastructure-as-code, with modern software engineering practicesDeep hands-on experience with Kubernetes, containerisation, and cloud-native deployment patternsStrong CI/CD experience and a track record of building deployment and release automationExperience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps)Practical experience with observability tooling (metrics, logging, tracing) and production incident responseExperience operating ML / LLM workloads in production (LLMOps, inference reliability, cost/performance management)Strong communication skills and the ability to set standards other engineers adoptIndustry-recognised container / Kubernetes certification (e.g., Certified Kubernetes Application Developer (CKAD), or similar)Masters degree in Computer Science, Engineering, or a related technical field (or equivalent applied experience)Site Reliability Engineering (SRE) experience and familiarity with reliability practices (SLOs, error budgets)Experience within financial services technologyFamiliarity with JPM-internal platform, cloud, and AI/ML infrastructure for internal candidates Responsibilities: Own the design and build of our platform: deployment pipelines, model serving, containerisation, orchestration, and environment managementSet the standard for reliability, observability, and operational excellence across our production AI/ML servicesBuild the tooling and paved paths that let AI engineers ship agentic AI and ML products safely and quicklyImplement platform-level security, secrets management, and access controls to firm-wide standardsPartner with data and AI engineers to productionise models, and coordinate with external infrastructure functions to reduce operational dependency and riskLead capacity, cost, and performance management for our compute and inference workloadsMentor platform and DevOps engineers and set engineering standards through design and code reviewChampion our culture of diversity, opportunity, inclusion, and respect Technologies: Agentic AIAICI/CDCloudDevOpsSupportKubernetesLLMMachine LearningMLOpsModel ServingPythonSecurityNetwork More:
hackajob is partnering directly with JPMorganChase to hire for this role. We are seeking a hands-on Platform Engineer - Senior VP to join our International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team. In this role, you will design and own the platform, tooling, and infrastructure that our agentic AI and machine learning products depend on, helping us move from individual use cases to multiple production platforms. This Senior VP-level position reports to the Head of AI, IPB Tech. J.P. Morgan is a global leader in financial services, providing strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. We value diversity and inclusion, support reasonable accommodations, and are part of the J.P. Morgan Asset & Wealth Management team, which delivers investment management and private banking solutions across global asset classes and wealth needs.
last updated 37 week of 2026