Job Description

Join us to advance your software engineering career while building impactful technology solutions. Grow your skills and make a difference with a collaborative team.

As a Manager of Software Engineering at JPMorgan Chase within Corporate Technology , you will lead the design, development, and delivery of innovative software solutions.

Job Responsibilities

• Lead the design, development, and delivery of innovative software solutions, solving complex problems with creative and forward-thinking approaches
• Build and maintain high-quality, secure, and production-grade code, while mentoring and reviewing the work of other engineers
• Drive architecture decisions to ensure scalability, resiliency, and zero-downtime deployments
• Identify opportunities to automate operational processes and eliminate recurring issues, improving platform stability and efficiency
• Develop and implement data-intensive and statistical solutions using Java/Scala on large-scale datasets
• Design and build AI-enabled applications, including AI Agents and agentic workflows
• Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns 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 and support capacity unlock initiatives.
• Work across hybrid data ecosystems (AWS, Databricks, Kubernetes)
• Ensure code quality through unit testing, integration testing, and continuous validation practices
• Collaborate with cross-functional teams to deliver end-to-end solutions aligned with enterprise standards

Required Qualifications, Capabilities, and Skills

• 10+ years of hands-on experience in software engineering with formal training or equivalent practical expertise
• Strong proficiency in Java and Spring Boot, with working knowledge of SQL and modern front-end frameworks (e.g., React)
• Demonstrated experience in designing scalable, secure, and resilient distributed systems
• Strong understanding of modern architecture patterns (microservices, event-driven, API-first)
• Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.
• Experience with CI/CD pipelines, containerization (Docker, Kubernetes/ECS/EKS), and Infrastructure as Code
• Expertise in API design (REST, GraphQL) and integration patterns
• Hands-on experience building applications on AWS or other public cloud platforms
• Experience with Generative AI systems, including: (Retrieval-Augmented Generation) architecture, AI orchestration frameworks (LangChain, LlamaIndex, etc.) and LLM evaluation frameworks and responsible AI practices (guardrails, content filtering)

Preferred Qualifications, Capabilities, and Skills

• Deep expertise in Java, object-oriented design, and system design
• Experience with ElasticSearch, Oracle, MongoDB, and modern data platforms
• Proven experience building AI-enabled applications and agentic architecture
• Experience developing reusable AI Agent skills/frameworks to accelerate engineering teams