Principal Software Engineer — Cloud Agentic AI Platform

Join us to drive innovation in cloud application architecture and platform engineering. You will shape how enterprise applications are designed, built, and operated, making a direct impact on our technology landscape. We offer opportunities for career growth, hands-on technical leadership, and collaboration with talented teams. Your expertise will help us modernize platforms and empower developers. Experience a culture that values creativity, inclusivity, and technical excellence.

Job Summary:
As an Executive Director, Principal Software Engineer in Infrastructure Platform Cloud Foundations Applied Architecture at JPMorganChase, you will lead the design and delivery of scalable, resilient, and secure cloud-native applications and platforms on public cloud. You will define reference architectures, well-architected patterns, and platform standards, while remaining deeply hands-on across design and delivery. You will partner with architects, platform teams, and stakeholders to translate strategy into actionable technical roadmaps. Your role will include mentoring and coaching engineering talent, and applying generative and agentic AI to enhance workflows and productivity.

Job Responsibilities:

• Lead the design and delivery of cloud-native applications and platforms on public cloud (AWS/Azure/GCP)
• Define standards for and enable generative AI and agentic AI features for multi-cloud management, including intelligent automation
• Architect microservices, event-driven systems, APIs, and distributed cloud applications
• Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale, while defining guardrails for validation, security, resiliency, and reuse across teams.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Embed shift-left architecture controls, guardrails, and reusable patterns into workflows
• Drive operational excellence through monitoring, logging, tracing, and SRE practices
• Translate enterprise architecture principles into actionable platform capabilities

• Partner with architects, engineering, product, risk, security, and business stakeholders

   

Required Qualifications, Capabilities, and Skills:

• Demonstrate deep, hands-on expertise in public cloud (AWS, Azure or GCP) cloud application architecture and platform engineering
• Apply best practices such as Well-Architected Frameworks across compute, storage, networking, serverless, containers, API Gateway, messaging, and data
• Build internal developer platforms, self-service capabilities, and reusable patterns
• Design distributed systems, event-driven architectures, REST/gRPC APIs, and resilient cloud applications
• Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
• Proficient in modern programming languages (Python, Java, or Go) and cloud-native frameworks
• Embed architecture guidance, governance controls, and policy-as-code into workflows
• Drive observability, operational excellence, and cost optimization
• Lead teams and set architecture direction as a credible technical authority
• Apply generative and agentic AI to engineering workflows, including prompt engineering, RAG, LLM orchestration, and AI-assisted developer tooling
• Advanced fluency and proficiency with AI coding assistants (e.g. Claude Code) and Agentic Runtime environments (e.g. Agent Runtime / AgentCore / Agent Service)

Preferred Qualifications, Capabilities, and Skills:

• Experience across at least two of the major public cloud service providers, including distributed systems at scale
• Implement cloud security guardrails and ensure enterprise data privacy
• Architecture experience in financial services or highly regulated environments
• Familiarity with structured engineering models e.g Spec-Drive & Test-Driven Development
• Open agentic frameworks, including building custom MCP servers or tools