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Salary
≈ $75k – $149k per year (Estimated)
Location
In office (Plano)
Seniority
Junior

Confirmed on the employer's own hiring board on Oct 6, 2026. First seen by Alion on Oct 6, 2026. The Infatuation scores A on the Alion truth index.

Overview
Company
Impact
Profile match
The Infatuation is a restaurant discovery and review publication headquartered in New York, publishing guides, ratings and recommendations on where to eat in cities across the US, the UK and beyond. Founded in 2009, it has been owned by JPMorgan Chase since 2021 and runs editorial teams in cities such as New York and London, with its content also tied to Chase dining benefits. Its own hiring centres on staff writers, editors, video and social producers, audience and partnerships staff, and product and engineering roles for its guides and app.

Kick-start your software engineering career as an entry-level Software Engineer I. Be part of a team that is pushing the boundaries of what's possible.

As a Software Engineer I at JPMorganChase within Asset & Wealth Management, you are part of an agile team that works to enhance, design, and deliver the software components to the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an entry-level member of a software engineering team, you execute basic software solutions through the design, development, and troubleshooting of a single technical area within a business function, while gaining skills and experience to grow within your role.

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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