Summary
✨ AI‑Generated
Design, build, and deliver secure, scalable systems for agent-driven business interactions. You will contribute to AI agent platforms as well as the data and machine-learning pipelines that power them, working in an agile environment with a strong emphasis on innovation, collaboration, and operational reliability.
Highlights
Opportunity to build secure, scalable agentic commerce systems at the intersection of software engineering, data, and machine learning. The role involves AI agent platforms, data pipelines, innovation, collaboration, and operational excellence.
Description
Job Description
Are you ready to push the boundaries of what's possible in payments technology? At JPMorganChase, you'll join a collaborative team where your ideas drive real impact.
You'll have the opportunity to grow your career, work with cutting-edge AI and machine learning, and help deliver trusted, market-leading products.
We value diversity, inclusion, and continuous learning—your contributions matter here.
As a Software Engineer III in Payments Technology within the Commercial and Investment Bank, you will design, build, and deliver secure, scalable agentic commerce solutions.
You'll work on B2B agent platforms that negotiate, onboard, and communicate with corporate suppliers, as well as the data and machine learning pipelines that power these agents.
You will contribute to NEO, our governed agent platform, and help shape the future of payments technology.
You'll be part of an agile team that values innovation, collaboration, and operational excellence.
Job Responsibilities
Execute software solutions, design, development, and technical troubleshooting for agent components, including orchestration logic, agent tools, and task queues for autonomous workflowsBuild and maintain MCP (Model Context Protocol) servers that provide agents secure access to CRM, supplier directory, and payments data sourcesDevelop secure, high-quality production code in Python, and review and debug code written by othersBuild data pipelines and feature engineering jobs on Databricks to prepare payments data for model training and agent retrievalContribute to the MLOps path for optimization and prediction models, including training jobs, automated tests, and promotion of model artefacts from development through UAT to productionWrite evaluations for agent behaviour (offline test sets, regression suites in CI/CD, LLM-as-judge checks) and instrument services with OpenTelemetry tracingApply enterprise-authorized AI-assisted development tools to improve code quality and delivery speed, validating AI outputs for correctness, performance, and securityIdentify opportunities to eliminate or automate remediation of recurring issues to improve operational stability of agents and model servicesFoster a team culture of diversity, opportunity, inclusion, and respect
Required Qualifications, Capabilities, And Skills
Formal training or certification in software engineering concepts and applied experienceHands-on practical experience in system design, application development, testing, and operational stabilityProficiency in Python and coding in one or more additional languages (e.g., Java, TypeScript, SQL)Experience building and consuming APIs and event-driven services in a cloud environmentExperience with data processing frameworks such as Apache Spark and working with large structured datasetsWorking knowledge of LLM-based application development, including prompting, tool calling, retrieval, and evaluationExperience using approved AI-assisted software development tools, with sound judgement on validating outputsUnderstanding of responsible AI use in engineering workflows, including data sensitivity and secure handling of inputs and outputsSolid understanding of agile methodologies such as CI/CD, application resiliency, and securityPractical cloud native experience (AWS preferred), including containers and Kubernetes
Preferred Qualifications, Capabilities, And Skills
Experience with agent frameworks (e.g., Google ADK, LangGraph) and agent protocols such as MCP, A2A, or AG-UIExperience with Databricks, MLflow, and Delta Lake or Apache IcebergExposure to model serving on Kubernetes and to model monitoring (drift, latency, accuracy)Familiarity with CRM platforms such as Salesforce and their APIsExposure to payments, commercial card, or supplier onboarding (KYC) processesFamiliarity with Terraform and infrastructure as code
ABOUT US
J.P.
Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors.
Our first-class business in a first-class way approach to serving clients drives everything we do.
We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success.
We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.
We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
Visit our FAQs for more information about requesting an accommodation.
About The Team
J.P.
Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments.
Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries.
The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.