oracle
Software Engineer I
JPMorgan Chase
Plano, USA
Full-time
Mid
Onsite
Discovered 2 weeks ago
Full Job Posting
Job responsibilities
- Executes basic software solution design, development, and technical troubleshooting, breaking down routine technical tasks to troubleshoot and solve issues
- Uses enterprise-authorized AI capabilities within the work environment to accelerate design comprehension and coding support (e.g., drafting unit tests and documentation), validating outputs and handling data according to sensitivity and security requirements.
- Writes secure and high-quality code using the syntax of at least one programming language with peer guidance
- Interprets architecture and design representations as well as nonfunctional requirements to develop secure, stable software against a defined architecture
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
- 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
- Actively applies automation to reduce manual toil in the Software Development Life Cycle and addresses basic code quality issues
- Gathers, analyzes, and synthesizes basic data sets in service of technical troubleshooting and generating insights to drive continuous improvements
- Applies reuse-first, AI-assisted practices within SDLC/toolchain automation to reduce manual toil while maintaining security, resiliency, and traceability/auditability expectations.
Required qualifications, capabilities, and skills
- Baseline knowledge of software, applications and technical processes within a given technical discipline
- Working knowledge of using enterprise-authorized AI capabilities within the work environment to support software engineering workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted code and technical recommendations before use, escalating when uncertain and following security and data handling requirements.
- Demonstrated experience leading effective use of approved AI-assisted software development tools (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 engineers on safe, compliant adoption within delivery practices
- Ability to work in large, collaborative teams to achieve organizational goals, with a passion to build an inclusive and innovative culture
- Demonstrated ability to code in one or more languages
- Understanding of software skills such as business analysis, development, maintenance, and software improvement
- Proficiency in developmental toolsets
Preferred qualifications, capabilities, and skills
- Exposure to cloud technologies
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