The role
From JPMorgan Chase's own posting.
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