Lead Software Engineer - Data - Agentic Commerce

JPMorgan Chase & Co.; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

JPMorgan Chase & Co. in London is seeking a Lead Software Engineer for Payments Technology to design, develop and deliver trusted tech products. You will own key components of B2B agentic commerce agents end-to-end, from multi-agent negotiation to production ML model workflows, ensuring secure, scalable services.

You will drive AI-assisted engineering practices, implement CI/CD for models, and collaborate across teams to advance AI-powered payments solutions.

Qualifications

• Formal training or certification in software engineering concepts.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Advanced proficiency in Python and proficiency in one or more additional languages (e.g., Java, TypeScript).
• Experience shipping LLM-based applications or agents to production, including tool calling, retrieval, and evaluation.
• Experience productionizing ML models, including training pipelines, model registries, CI/CD for models, and serving behind APIs.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling.

Responsibilities

• Execute creative software solutions, design, development, and technical troubleshooting.
• Own the design and delivery of production agents, including orchestration, negotiation, supplier onboarding, and outreach.
• Build production paths for optimization and prediction models, including training, automated testing, and serving on Kubernetes.
• Design agent workflows that ensure pricing, eligibility, and policy decisions remain in deterministic services.
• Develop secure, high-quality production code and review and debug code written by others.
• Establish evaluation and observability for agents and models, including regression suites, scoring, traces, and performance monitoring.
• Prepare agents and models for model risk review, producing documentation, test evidence, and controls.
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
• Apply knowledge of tools within the Software Development Life Cycle toolchain to enhance automation.
• Identify opportunities to eliminate or automate remediation of recurring issues.
• Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials.

Skills

Python

Java

TypeScript

LLM production

CI/CD for ML

Kubernetes

Cloud (AWS)

Security best practices

Responsible AI

Agile methodologies

Observability

Education

Bachelor’s degree in Computer Science or equivalent

Tools

Kubernetes

Amazon EKS

Databricks

MLflow

Spark

Delta Lake

Apache Iceberg

OpenTelemetry

LangGraph

Job description

Join us to shape the future of payments technology and agentic commerce. You will have the opportunity to build impactful solutions, collaborate with talented teams, and advance your career in a dynamic environment. We value creativity, inclusivity, and continuous learning, empowering you to push boundaries and deliver market-leading products. Experience the excitement of working with cutting-edge AI and ML tools while making a difference in the financial industry.

As a Lead Software Engineer in Payments Technology within the Commercial and Investment Bank, you will play a pivotal role in designing, developing, and delivering trusted technology products. You will own major components of our B2B agentic commerce agents end to end, from multi-agent negotiation and onboarding to production ML model workflows. You will help drive secure, stable, and scalable solutions, foster a collaborative team culture, and contribute to the advancement of AI-powered payments. Your expertise will directly impact our technology and the clients we serve.

Job Responsibilities:

• Execute creative software solutions, design, development, and technical troubleshooting
• Own the design and delivery of production agents, including orchestration, negotiation, supplier onboarding, and outreach
• Build production paths for optimization and prediction models, including training, automated testing, and serving on Kubernetes
• Design agent workflows that ensure pricing, eligibility, and policy decisions remain in deterministic services
• Develop secure, high-quality production code and review and debug code written by others
• Establish evaluation and observability for agents and models, including regression suites, scoring, traces, and performance monitoring
• Prepare agents and models for model risk review, producing documentation, test evidence, and controls
• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed
• Apply knowledge of tools within the Software Development Life Cycle toolchain to enhance automation
• Identify opportunities to eliminate or automate remediation of recurring issues
• Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials

Required Qualifications, Capabilities, and Skills:

• Formal training or certification in software engineering concepts
• Hands-on experience delivering system design, application development, testing, and operational stability
• Advanced proficiency in Python and proficiency in one or more additional languages (e.g., Java, TypeScript)
• Experience shipping LLM-based applications or agents to production, including tool calling, retrieval, and evaluation
• Experience productionizing ML models, including training pipelines, model registries, CI/CD for models, and serving behind APIs
• Demonstrated experience leading effective use of approved AI-assisted software development tools
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling
• Proficiency in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In-depth knowledge of the financial services industry and IT systems
• Practical cloud native experience
• Proficiency with Kubernetes and Amazon EKS, micro-VM isolation, and sidecar patterns, with hands-on experience applying security at multiple layers

Preferred Qualifications, Capabilities, and Skills:

• Experience with agent frameworks and protocols (Google ADK, LangGraph, MCP, A2A, AG-UI)
• Experience with Databricks, MLflow, Spark, and Delta Lake or Apache Iceberg
• Experience serving models on Kubernetes, including GPU workloads and fine-tuned small language models
• Experience with optimization or pricing models and exposing them as services
• Experience with fine-grained authorization and OpenTelemetry