Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector, Infrastructure Platforms team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Required qualifications, capabilities, and skills

Provide technical guidance and direction to support business objectives, collaborating with technical teams, contractors, and vendors. Develop secure, high-quality production code, and review and debug code written by others. Influence product design, application functionality, and technical operations through informed decision-making. Advocate for firmwide frameworks, tools, and practices within the Software Development Life Cycle. Promote a culture of diversity, equity, inclusion, and respect within the team. Architect and deploy secure, scalable cloud infrastructure platforms optimized for AI and machine learning workloads. Collaborate with AI teams to translate computational needs into infrastructure requirements. Monitor, manage, and optimize cloud resources for performance and cost efficiency. Design and implement continuous integration and delivery pipelines for machine learning workloads. Develop automation scripts and infrastructure as code to streamline deployment and management tasks.

Required Qualifications:

Formal training or certification in software engineering concepts with 5+ years of applied experience. Hands-on experience in system design, application development, testing, and operational stability. Proficiency in programming languages such as Python and/or Golang. Ability to independently tackle design and functionality problems with minimal oversight. Background in Computer Science, Computer Engineering, Mathematics, or a related technical field. Strong knowledge of cloud computing delivery models (IaaS, PaaS, SaaS) and deployment models (Public, Private, Hybrid Cloud). Proficiency in Linux environments, including scripting and administration. Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference. Experience in solutions design and engineering, containerization (Docker, Kubernetes), and cloud service providers (AWS, Azure, GCP). Experience with Infrastructure as Code (Terraform, CloudFormation) and automation tools (Ansible, Chef, Puppet). Deep understanding of cloud component architecture: Microservices, Containers, IaaS, Storage, Security, and routing/switching technologies.

Preferred Qualifications:

Foundational understanding of NVIDIA GPU Infrastructure software (e.g., NVIDIA DCGM, BCM, Triton Inference). Hands-on experience with ML frameworks such as PyTorch, TensorBoard. Experience with observability tools like Prometheus, Grafana. Experience in ML Ops and associated tooling like MLflow. Experience with High Performance Computing and Machine Learning frameworks such as vLLM, Ray.io, Slurm. Strong background in network architecture, database programming (SQL/NoSQL), and data modeling. Familiarity with cloud data services and big data processing tools.

FEDERAL DEPOSIT INSURANCE ACT:

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.