Senior Lead AI Platform Engineer

JPMorgan Chase & Co.

Plano (TX)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

JPMorgan Chase & Co. in Jersey City seeks a Senior Lead Software Engineer to build AI foundation services for GenAI and ML at enterprise scale.

You will lead hands-on delivery of secure, cloud-native platform capabilities (Kubernetes/CI/CD/IaC) and partner with application teams to create reusable integrations and onboarding assets. As a Senior Lead Software Engineer, you will join an agile team within the AIML Data Platforms to enhance, build, and deliver trusted technology products in a

Qualifications

Hands-on experience designing, building, testing, and operating production software systems, distributed services, or platform capabilities.
Experience with AI/ML platform capabilities, model serving, hosting, data access patterns, and platform integrations.
Experience building cloud-native applications or platform services using Kubernetes, containers, CI/CD, IaC, and modern practices.
Proficiency in Python, Java, or Go with ability to deliver production-grade code.
Ability to translate business requirements into technical designs and delivery plans.
Knowledge of performance engineering, monitoring, and reliability practices.
Experience applying secure-by-design engineering practices and secrets management.
Experience coaching teams in responsible AI use and compliant patterns.

Responsibilities

Designs, builds, integrates, and optimizes AI Foundation Services infrastructure components for GenAI and AI/ML platforms with production-grade delivery.
Partners with Lines of Business application teams to co-develop reusable AI/ML foundations and platform adoption patterns.
Translates business requirements into technical designs, implementation plans, and engineering deliverables for successful launches.
Contributes to non-functional requirements, test plans, runbooks, observability, and production readiness reviews.
Builds reusable assets such as reference implementations, deployment templates, and onboarding guides for model hosting platforms.
Drives adoption and governance of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
Applies SDLC tools and AI-assisted development capabilities to improve automation at scale.
Implements durable, maintainable code and platform capabilities reusable by multiple teams.
Collaborates across product, platform, security, and infrastructure to resolve complex issues.
Participates in design reviews and incident analyses to improve reliability and developer experience.