IT & Software

Senior Lead Software and Data Engineer - Agentic Commerce

JP Morgan Chase

London · Greater London · United Kingdom

Overview

In this role you will set the architectural direction for B2B agentic commerce and ML-powered tools, guiding a London team to deliver secure, scalable payment solutions at a global bank. You’ll shape engineering standards, drive AI-assisted development, and collaborate with cross-functional teams to advance secure, high-quality technology products. The opportunity combines leadership, technical direction, and hands-on delivery to impact payments at scale.

Responsibilities
  • Set technical direction and reference architecture for B2B agentic commerce and multi-agent communication
  • Design information barriers and authorization for agents acting for different counterparties
  • Define MLOps architecture for agent tools (training, environment promotion, model registry, serving, monitoring, retraining)
  • Establish engineering standards for agent quality, safety, and risk evidence
  • Develop secure, high-quality production code and perform reviews
  • Partner with platform, risk, and client-facing teams to integrate external agents
  • Drive adoption of enterprise-authorized AI-assisted engineering practices and validation standards
  • Apply SDLC toolchain knowledge including AI-assisted development and automation
  • Identify opportunities to automate recurring issues for operational stability
  • Lead evaluation sessions with vendors and internal teams on architectural designs
Key requirements
  • Formal training or certification in software engineering concepts with advanced applied experience
  • Hands-on system design, application development, testing, and operational stability
  • Advanced proficiency in Python
  • Architect and ship production LLM agents or multi-agent systems
  • Design end-to-end ML platforms or MLOps pipelines
  • Expertise in secure distributed systems (identity, authorization, service-to-service trust)
  • Lead with AI-assisted software development tools and validate AI outputs
  • Understand responsible AI use, data sensitivity, and secure engineering workflows
  • Proficiency across the Software Development Life Cycle
  • Advanced understanding of agile methods (CI/CD, resiliency, security)
  • Knowledge of financial services IT systems
  • leadership
  • collaboration
  • innovation
  • Python
  • LLM agent architectures
  • MLOps pipelines

Reference: WJ-747_30920373

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