Senior Lead Software and Data Engineer - Agentic Commerce

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

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