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
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