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Salary
≈ $27k – $56k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 5+ years exp

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.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank, Securities Services Technology, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Develops and maintain high-quality, secure applications using Python and AWS
  • Creates architecture and design deliverables, lead design and architecture reviews, own end-to-end delivery. Integrates AIML solutions into complex, domain specific operations processing systems
  • Leads code reviews, design discussions, and agile planning sessions. Collaborates with SRE and production monitoring teams to ensure system reliability and performance
  • Contributes to software engineering communities of practice and technology events
  • Embraces continuous learning, creative problem solving, and a can-do attitude
  • Leads evaluation and selection of open source and internal software to determine best fit
  • Partners with existing systems teams on cross-app design; align interfaces and ship end-to-end solutions
  • Manages small team of engineers whilst remaining hands on, setting engineering standards
  • 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.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • Proven hands-on experience in Python application development
  • Proven hands-on experience developing, debugging and maintaining production applications
  • Solid understanding of software development best practices, including version control, testing, and CI/CD
  • Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
  • Experience working on AIML systems and/or prior experience collaborating with data scientists
  • Track record of designing, building, and delivering maintainable, extensible applications into production environments

Preferred qualifications, capabilities, and skills

  • Experience with Cloud services, Infrastructure as Code (IaC) and containerized application development
  • Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock
  • Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and LLMs
  • Experience working on AIML systems and/or prior experience collaborating with data scientists
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