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Based on 240 similar postings.
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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1243 open roles
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As a Sr Lead Software Engineer(AI, Data Cloud) within Corporate Technology – Chief Technology Office, you will serve as a senior individual contributor and technical leader on an agile team. You will drive critical technology solutions by contributing production Python code and owning end-to-end delivery from design through production operations. Your daily work involves leading system architecture for ML workflows, designing agentic AI capabilities for workload optimization, and building reusable APIs and SDKs. You will utilize AWS, Databricks, Terraform, and containerized platforms like EKS to automate infrastructure and CI/CD pipelines. Key responsibilities include managing data transformation patterns, feature management, and LLM orchestration while ensuring platform reliability through SLOs. You will partner with data scientists to deliver measurable outcomes in a secure, scalable, and stable environment.
Write production code primarily in Python and own end-to-end delivery from design through production operations.
Lead system and platform architecture for components supporting end-to-end ML workflows and model serving.
Design and develop agentic AI capabilities to analyze workloads and generate optimization recommendations.
Build and maintain reusable APIs and SDKs to enable consistent platform adoption across teams.
Automate infrastructure provisioning, configuration, and CI/CD pipelines using Infrastructure as Code.
Ensure platform reliability and cost efficiency through proactive monitoring, incident response, and root-cause analysis.
Drive adoption of AI-assisted engineering practices to improve code quality and delivery speed.
Produce architecture and design artifacts that align with enterprise standards and best practices.
What we're looking for
Formal training or certification on software engineering concepts and 5+ years of applied experience.
Demonstrated experience in system design, application development, testing, and operational stability for distributed systems and platform services.
Strong hands-on depth in Python, including building and maintaining APIs/SDKs and performing high-quality code and design reviews.
Experience delivering platforms involving Generative AI, including LLM orchestration patterns, agentic AI frameworks, and production-grade evaluation and monitoring.
Demonstrated experience with enterprise-authorized AI-assisted development tools and establishing team norms for validation and quality.
Practical experience with AWS, containerized platforms (e.g., EKS/ECS), and Terraform or equivalent Infrastructure as Code.
Databricks experience, including building and operating data/ML workloads, pipelines, and orchestration with ML workflows.
Comprehensive knowledge of the Software Development Life Cycle, agile delivery, CI/CD, and modern engineering quality controls.