Lead AI & Data Systems Engineer (Production)

JPMorganChase; Greater London; Sur place; GBP 120 000 - 170 000; Plein temps

Résumé du poste

JPMorganChase in London is seeking a Lead Software Engineer to own major components of our B2B agentic commerce agents end to end. You will work within the Commercial & Investment Bank, Payments Technology, delivering secure, scalable technology products.

You will lead design and delivery of production agents, train and serve ML models, implement CI/CD, and ensure observability and security across the stack in a fast-paced, cutting-edge environment.

Qualifications

• Formal training or certification on software engineering concepts and advanced applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Advanced, strong hands-on development experience in Python and/or Java, and proficient in one or more additional languages (e.g., TypeScript, SQL).

Responsabilités

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Owns the design and delivery of one or more production agents running on NEO, including their tools, memory, guardrails, and evaluations.
• Builds the production path for optimization and prediction models: training on Databricks, automated testing in each environment, promotion through stages, and serving on Kubernetes as APIs.

Connaissances

Python

Java

Kubernetes

AWS

Databricks

MLflow

CI/CD

OpenTelemetry

OpenFGA/OpenPga

Outils

Kubernetes

EKS

KServe

Triton

Databricks

MLflow

Spark

Delta Lake

Description du poste

JPMorganChase in London is seeking a Lead Software Engineer to own major components of our B2B agentic commerce agents end to end. You will work within the Commercial & Investment Bank, Payments Technology, delivering secure, scalable technology products.

You will lead design and delivery of production agents, train and serve ML models, implement CI/CD, and ensure observability and security across the stack in a fast-paced, cutting-edge environment.