Lead Software Engineer - AI/ML Engineering, GPU ML Serving

Software Engineer III We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorgan Chase within the Commercial and Investment Banking team, you will be a key member of an agile team, designing and delivering secure, stable, and scalable technology products. You will implement critical technology solutions across multiple technical areas, supporting the firm's business objectives. Job Responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. 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. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Required Qualifications, Capabilities, and Skills Formal training or certification on software engineering concepts and 5+ years applied experience Professional software development experience, with emphasis on ML systems. Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security. Responsible for AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Experience contributing to the design and development of scalable systems and services (e.g., web services, APIs) Proficiency in Python, including experience with ML frameworks (e.g., TensorFlow, PyTorch, or similar) Experience with cloud-native technologies (e.g., Docker, Kubernetes) Experience with one or more public cloud platforms (AWS, GCP) Experience with system design fundamentals (e.g., reliability, scalability, performance tradeoffs) Experience working with distributed systems concepts, microservices architectures, Cassandra or equivalent NoSQL databases Mentorship and technical leadership experience, including setting engineering standards and elevating overall team quality Preferred Qualifications, Capabilities, and Skills Working knowledge of additional languages such as Java and/or C++ Exposure to deploying or operating GPU workloads in Kubernetes environments Exposure to ML model serving frameworks (e.g., TorchServe, TensorFlow Serving, Triton Inference Server) Familiarity with distributed training and inference systems Awareness of model compression techniques and edge deployment concepts Familiarity with API management concepts, Domain-Driven Design (DDD) and working in Agile development environments Chase