Software Engineer II

Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center -  all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment.
As a  Software Engineer II at JPMorgan Chase within the International Consumer Bank, you will play a crucial role in this initiative, dedicated to delivering an outstanding banking experience to our customers. You will work in a collaborative environment as part of a diverse, inclusive, and geographically distributed team. We are seeking individuals with a curious mindset and a keen interest in new technology. Our engineers are naturally solution-oriented and possess an interest in the financial sector and focus on addressing our customer needs. We work in teams focused on specific products and projects, providing opportunities to engage in areas such as fraud & financial crime prevention, identity services, money transfers, card payments, lending, customer onboarding, core banking, insurance products, rewards campaigns, and servicing innovations.

Job Responsibilities

• Execute well-defined components of cloud-native platform services, AI applications, and supporting tooling with minimal guidance. 
• Contribute to reusable platform components, libraries, and templates that other teams across ICB compose into their own AI use cases. 
• Apply established resilient patterns within your services; escalate risks or gaps to senior engineers. 
• Develop secure code to protect our customers and ourselves from malicious actors. 
• Investigate and remediate issues within your scope; escalate appropriately; contribute to preventing recurrence. 
• Support release processes aiming for zero downtime, following team standards. 
• Contribute to observability for the platform components and applications you work on; raise anomalies for squad resolution. 
• Contribute to ensuring the platform components and applications you work on meet the needs of the developers and teams who use them, within your scope. 
• Maintain and continuously improve the platform components and AI applications you ship. 
• Embed controls, compliance, and security into the components and applications you build, so that teams adopting them meet their obligations by default.
• Provide well-structured, timely updates on Jira stories to keep the squad informed of progress and issues.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team. 
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
   

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and applied experience. 
• Recent hands-on professional experience as a back-end software engineer. 
• Experience coding in recent versions of Java and Python programming languages. 
• Experience designing and implementing effective tests (unit, component, integration, end-to end, performance, etc.). 
• Excellent written and verbal communication skills in English. 
• Familiarity with advanced AI and ML concepts, such as model serving, feature retrieval, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP). 
• Strong interest in building generative AI applications and tooling. 
• Experience with cloud technologies and distributed systems, RESTful APIs, and web technologies
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security. 
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
   

Preferred Qualifications, Capabilities, And Skills

• Background in STEM with exposure to machine learning systems. 
• Experience with MLOps frameworks and platforms like MLflow, Amazon SageMaker, Databricks, BentoML, or Arize is a plus. 
• Experience with AI frameworks like LangChain, LangGraph, or Pydantic AI is a plus. 
• Hands-on experience with cloud computing platforms like AWS, Azure, or GCP. 

• Experience working in a highly regulated environment or industry.
   

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