Senior Lead Software Engineer, AI Platforms

About the role

Be an integral part of an agile engineering team that is constantly pushing the boundaries of what is possible across cloud, infrastructure, and AI/ML platforms. As a Senior Lead Software Engineer within the Corporate Sector, Infrastructure Platforms team, you will design, build, and operate secure, scalable, and resilient infrastructure platforms that power enterprise AI/ML workloads. You will partner closely with AI/ML engineering teams, platform teams, product owners, and infrastructure stakeholders to translate complex compute, storage, networking, GPU, and scalability requirements into production‑ready platforms for multi‑GPU and multi‑node model training, while advancing automation, developer productivity, responsible AI‑assisted engineering practices, and operational excellence.

Responsibilities

• Design, develop, test, and deliver secure, high‑quality production code; review, debug, and improve code written by others.
• Architect, build, and operate secure, scalable cloud infrastructure platforms optimized for multi‑GPU and multi‑node AI/ML training workloads.
• Partner with AI/ML, data science, and platform engineering teams to translate compute, storage, networking, GPU, and scalability needs into robust infrastructure requirements and platform capabilities.
• Drive technical design decisions that influence product architecture, application functionality, infrastructure strategy, and operational effectiveness.
• Monitor, manage, and optimize cloud and GPU infrastructure resources for performance, reliability, utilization, scalability, and cost efficiency.
• Build and maintain CI/CD pipelines, automation frameworks, and infrastructure‑as‑code solutions to streamline ML platform deployment, operations, and lifecycle management.
• Provide technical leadership and guidance to engineers, contractors, and vendor partners, ensuring solutions align with business priorities, engineering standards, security expectations, and long‑term platform strategy.
• Apply deep knowledge of the Software Development Life Cycle (SDLC) toolchain, including enterprise‑approved AI‑assisted development and automation capabilities, to improve engineering productivity and automation at scale.
• Champion firm‑wide SDLC frameworks, engineering standards, secure coding practices, resiliency expectations, and operational best practices.
• Drive adoption and governance of approved AI‑assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes, establishing measurable validation standards and promoting reuse of proven patterns.

Requirements

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands‑on experience building highly scalable and highly available infrastructure for machine learning training and/or inference workloads.
• Solid system‑level understanding of GPU infrastructure, accelerators, high‑speed interconnects, distributed compute, and related platform technologies.
• Strong experience with Kubernetes and containerization technologies (Docker, cluster operations, workload scheduling, observability, production troubleshooting).
• Proficiency in at least one modern programming language such as Python, Go, Java, or C#.
• Demonstrated ability to independently solve complex design, scalability, reliability, performance, and functionality challenges with minimal oversight.
• Deep understanding of cloud component architecture, including microservices, compute, storage, networking, security, routing, and switching technologies.
• Experience leading effective use of enterprise‑authorized AI‑assisted software development tools for coding, code review, test acceleration, troubleshooting, and engineering productivity.
• 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 senior engineers on compliant usage patterns.
• Design, develop, test, and deliver secure, high‑quality production code; review, debug, and improve code written by others.

Preferred Qualifications

• Hands‑on experience with performance monitoring, production debugging, profiling, sampling, bottleneck analysis, and capacity optimization.
• Foundational understanding of NVIDIA GPU infrastructure software and ecosystem tooling (DCGM, BCM, NVIDIA drivers, CUDA, training libraries).
• Experience with MLOps platforms and tooling, such as MLflow or similar model lifecycle management solutions.
• Background in high‑performance computing, distributed systems, and ML frameworks, including distributed training, Ray.io, Slurm, or similar workload orchestration technologies.
• Strong knowledge of network architecture, including high‑throughput and low‑latency networking patterns for distributed compute and AI/ML workloads.
• Familiarity with cloud data services, big data processing platforms, Linux systems, and storage technologies used in large‑scale data and ML environments.
• Experience designing platforms that support model training, experiment tracking, feature pipelines, model serving, and scalable inference in enterprise environments.

About the team

Our Corporate Functions professionals cover a diverse range of areas from finance and risk to human resources and marketing. The corporate teams are essential to the company, ensuring that businesses, clients, customers, and employees are set up for success.

About the company

JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses, and many of the world’s most prominent corporate, institutional, and government clients. With a history spanning over 200 years, the firm leads in investment banking, consumer and small‑business banking, commercial banking, financial transaction processing, and asset management.

Benefits

• Comprehensive health care coverage.
• On‑site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching and additional employee programs.

Pay

The role offers a competitive total rewards package, including a base salary determined based on the role, experience, skill set, and location. Eligible employees may receive commission‑based pay and/or discretionary incentive compensation, paid in cash and/or forfeitable equity, in recognition of individual achievements and contributions.

This position is subject to Section 19 of the Federal Deposit Insurance Act; employment is contingent on JPMorgan Chase’s review of criminal conviction history, including pre‑trial diversions or program entries.