Senior Lead Software Engineer- AI Platform engineer

JPMorgan Chase & Co.; San Francisco (CA); On-site; USD 150,000 - 180,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Senior Lead Software Engineer to join the Corporate Sector, Infrastructure Platforms team. This role involves architecting secure, scalable cloud platforms optimized for AI/ML workloads and influencing product design through technical expertise. Candidates should possess over 5 years of experience in software engineering and be proficient in Kubernetes, Docker, and one programming language such as Python or Java.

The position emphasizes collaboration, cloud computing delivery models, and responsible AI use in engineering workflows, making it a critical role in driving business impact through technology.

Qualifications

• 5+ years of applied experience in software engineering.
• Hands-on experience in system design and application development.
• Strong knowledge of cloud computing delivery models.

Responsibilities

• Provide technical guidance aligned to business goals and collaborate effectively.
• Develop secure and high-quality production code.
• Architect and deploy scalable cloud platforms optimized for AI/ML workloads.

Skills

Python

Kubernetes

Docker

Machine Learning

Infrastructure as Code

Education

Formal training or certification in software engineering

Tools

Prometheus

Grafana

Job description

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.

Job Responsibilities

• Provide technical guidance aligned to business goals, collaborating with engineers, contractors, and vendors.
• Develop secure, high‑quality production code; review, debug, and improve others’ code.
• Influence product design, application functionality, and technical operations through informed decisions.
• Champion firmwide SDLC frameworks, tools, and best practices.
• Promote a culture of diversity, equity, inclusion, and respect.
• Architect and deploy secure, scalable cloud platforms optimized for AI/ML workloads.
• Partner with AI teams to translate compute needs into infrastructure requirements.
• Monitor, manage, and optimize cloud resources for performance and cost efficiency.
• Create CI/CD pipelines, automation, and infrastructure‑as‑code to streamline ML deployment and operations.
• Drive adoption and governance of approved AI‑assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes, while establishing measurable validation standards and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including approved AI‑assisted development and automation capabilities, to improve the value realized by automation at scale.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands‑on experience in system design, application development, testing, and operational stability.
• Strong experience with Kubernetes and containerization (Docker), including cluster operations and production troubleshooting.
• Proficiency in at least one programming language, such as Python, Go, Java, or C#.
• Ability to independently tackle design and functionality problems with minimal oversight.
• Strong knowledge of cloud computing delivery models (IaaS, PaaS, SaaS) and deployment models (Public, Private, Hybrid Cloud).
• Foundational understanding of machine learning concepts, including transformer architecture, ML training, and inference.
• Experience with Infrastructure as Code.
• Deep understanding of cloud component architecture: Microservices, IaaS, Storage, Security, and routing/switching technologies.
• Demonstrated experience leading effective use of enterprise‑authorized AI‑assisted software development tools within the work environment, 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 senior engineers/leads on compliant usage patterns and controls.

Preferred qualifications, capabilities, and skills

• Foundational understanding of NVIDIA GPU infrastructure software (e.g., DCGM, BCM, Dynamo Inference).
• Proficiency with observability tools like Prometheus and Grafana.
• Experience in ML Ops and related tooling, including MLflow.
• Background in high‑performance computing and ML frameworks (e.g., vLLM, Ray.io, Slurm).
• Strong knowledge of network architecture, database programming (SQL/NoSQL), and data modeling.
• Familiarity with cloud data services, big data processing tools, and Linux environments.

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 JPMorgan Chase’s review of criminal conviction history, including pretrial diversions or program entries.