We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Lead Software Engineer at JPMorgan Chase within the consumer and community banking technology team, you will be a senior technical leader responsible for driving the architecture, design, and delivery of enterprise-scale platforms and solutions. You will lead engineering teams, shape technical strategy, and champion innovation across full-stack development, cloud-native ecosystems, and emerging technologies including Generative AI. This role demands deep technical expertise, a passion for engineering excellence, and the ability to influence and mentor across the organization.
Job Responsibilities
- Define and drive the system design and architecture of enterprise-scale applications, ensuring scalability, resilience, security, and performance across the firm's technology landscape.
- Establish architectural standards, design patterns, and engineering best practices that align with JPMorganChase's strategic technology direction.
- Evaluate and adopt emerging technologies to maintain competitive advantage and operational excellence.
- Lead the development of high-performance, distributed platforms using Java, Spring Boot, and Event-Driven architectures (Kafka, event sourcing, CQRS).
- Drive full-stack development initiatives, encompassing backend services, APIs, and modern front-end experiences built with React and related UI/UX technologies.
- Architect and deliver solutions within hybrid cloud ecosystems, leveraging public cloud (AWS, Azure, GCP) and private cloud infrastructure.
- Champion container-based application development and orchestration using Kubernetes, Docker, and OpenShift within enterprise-grade ecosystems.
- Drive DevSecOps culture and practices, embedding security into CI/CD pipelines, infrastructure-as-code, automated testing, and deployment workflows.
- Ensure applications meet the firm's standards for security, compliance, and operational resilience.
- Lead the design and implementation of Agentic AI and Generative AI solutions, integrating large language models, AI agents, and intelligent automation into enterprise platforms.
- Collaborate with data science and AI/ML teams to bring innovative AI-driven capabilities to production at scale.
Required qualifications, capabilities and skills:
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Deep expertise in Java, Spring Boot, and microservices architectures, including event-driven and message-based systems (e.g., Kafka, RabbitMQ).
- Proven experience in full-stack development with modern UI/UX frameworks, particularly React (including state management, component design, and responsive design).
- Strong experience architecting and deploying applications in hybrid cloud environments (AWS, Azure, GCP, and on-premises infrastructure).
- Extensive experience with container-based platforms (Docker, Kubernetes, OpenShift) and cloud-native development patterns.
- Demonstrated expertise in DevSecOps practices, including CI/CD pipeline design, infrastructure-as-code (Terraform, Ansible), automated security scanning, and observability.
- Experience designing and delivering Agentic AI and/or Generative AI solutions in enterprise environments.
- Proven track record of leading platform development and engineering teams, including hiring, mentoring, and performance management.
- Expert-level ability in system design and architecture of large-scale, distributed, enterprise applications with high availability and fault tolerance.
- Strong communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences.
Preferred qualifications, capabilities and skills:
- Experience in the financial services industry or other highly regulated environments.
- Familiarity with AI/ML frameworks and tools (e.g., LangChain, LlamaIndex, OpenAI APIs, Hugging Face, TensorFlow, PyTorch).
- Experience with API gateway design, service mesh architectures (Istio, Envoy), and GraphQL.
- Knowledge of data engineering practices, real-time streaming, and analytics platforms.
- Experience contributing to or leading open-source projects.
- Advanced degree (MS or PhD) in Computer Science, Engineering, or a related field.