As a Sr. Lead of Software Engineering at JPMorganChase within the Payments Technology function, you will lead multiple technical teams, provide oversight to the activities of multiple departments, and collaborate across technical domains. We will rely on your expertise to promote the adoption and implementation of technical methods within various teams and aid us in remaining at the forefront of industry trends, best practices, and technological advances. This role provides an opportunity to influence and shape the technological landscape of our firm and contribute to our continuous growth and innovation in the Middle East.
Job responsibilities
- Solution and implement individual project priorities, deadlines and deliverables.
- Work closely with technology teams and internal end users to deliver solutions that drive a variety of trade businesses.
- Influences peer leaders and senior stakeholders across the business, product, and technology teams
- Optimize application for maximum performance, scalability and high availability.
- Ensure the technical feasibility of UI/UX designs.
- Build reusable code and libraries for future use.
- Deliver technical solutions that can be leveraged across multiple businesses and domains
- Champions the firm’s culture of diversity, equity, inclusion, and respect
- 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.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and expert applied experience.
- Experience of using a Test Driven Development and Domain Driven Development approach and associated testing frameworks.
- Proven strong hands-on experience in Java/J2EE development. Design, Develop and maintain java applications.
- Strong knowledge and experience with Hibernate ORM framework. Knowledge of database system and SQL. Experience in UNIX, Shell scripting.
- Detailed understanding of distributed and parallel processing environment and excellent in Data Structures, Algorithms and Design Patterns.
- 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.
- Working experience in one of the container orchestration frameworks like Docker Swarm or Open-shift/Kubernetes.
- Working experience on building stateless, SAAS/SOA and scalable applications/platforms.
- Shall have a good understanding on continuous monitoring frameworks such as ELK, Grafana, and Prometheus on distributed infra. Extensive experience with the spring framework (Spring boot, MVC, spring Transactions)
- Proficient understanding of code versioning tools, such as git/git-flow.
Preferred qualifications, capabilities, and skills
- Software delivery experience in Payments
- Working experience with one of functional programming: Scala, go, python
- Hands on knowledge on GWT, Mule ESB is a plus.
- Experience in persistence store; MongoDB, Graph DB, Big table
- Experience in several SDLC frameworks including but not limited to: Maven/Gradle, PIP, anaconda, Jenkins, Jira.
- Experience in the field of Machine learning, NLP, OCR.
- Open source contribution.