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 JPMorganChase within the Consumer & Community Banking Auto Technology 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
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain
- Applies 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
- Develops modular components for agentic systems to enable intelligent automation and orchestration within business platforms; continuously build, test, and maintain these components
- Containerizes and deploys agentic system components on cloud platforms (preferably AWS), strictly following established DevOps and infrastructure-as-code practices.
- Applies the latest advancements in agentic frameworks (such as LangGraph, Google ADK, AutoGen), LLMs, and GenAI to assigned tasks and features by staying up to date with industry developments
- Documents design decisions, implementation details, and results with clearly communicated progress and technical concepts to team members and stakeholders
- Ensures code quality, security, and compliance by conducting thorough testing, peer reviews, and adhering to best practices
- Builds strong partnerships with similar teams across locations, as well as with other internal and external stakeholders, to facilitate effective stakeholder management
- Owns individual workstreams and Jira stories, consistently delivering high-quality code and features as part of broader AI/ML initiatives
- Collaborates closely with team members to integrate agentic capabilities into existing systems and actively support solution delivery
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) 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
- Hands-on experience developing and delivering agentic system components or autonomous AI features in production environments
- Strong Python and Java programming skills, with a focus on secure, modular, scalable, and maintainable code
- Experience with cloud platforms (AWS), containerization (Docker), and infrastructure as code (Terraform)
- Familiarity with agentic frameworks (LangGraph, Google ADK, AutoGen) and integrating AI capabilities into business processes
- Ability to work collaboratively in agile, cross-functional teams and deliver on assigned workstreams
- Excellent problem-solving, communication, and documentation skills
- Ability to lead and manage senior resources, guiding them on assignments and finding the right support for them when they are stuck
Preferred qualifications, capabilities, and skills
- Experience with Large Language Models (LLMs), GenAI, and retrieval-augmented generation (RAG)
- Exposure to agentic system design patterns, orchestration, and workflow automation
- Ability to design and evaluate autonomous system features aligned with business goals
- Experience with additional cloud services (EKS, S3, RDS, CloudFormation)