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Salary
≈ $26k – $57k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 10+ years exp

Confirmed on the employer's own hiring board on Sep 30, 2026. First seen by Alion on Sep 30, 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 Consumer & Community Banking Digital Channels, you are an integral part of an agile team that designs, builds, and delivers trusted, market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for promoting critical technology solutions across multiple technical domains and business functions, ensuring they align with and advance the firm’s strategic objectives.

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • 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.
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

  • Formal training or certification in software engineering concepts with 5+ years of applied experience.
  • 10+ years of professional software engineering experience building and operating backend services using Java (11/17+) and Spring Boot (Spring MVC/WebFlux, Spring Security).
  • Proven experience designing and delivering distributed systems using patterns such as caching, idempotency, retries, rate limiting, and circuit breakers.
  • Hands-on AWS experience across multiple services, including ECS/EKS/Lambda, API Gateway/ALB, VPC, and Route 53.
  • Experience with data persistence and storage solutions including RDS/Aurora/PostgreSQL, DynamoDB, and S3, plus caching with ElastiCache.
  • Experience implementing event-driven and streaming architectures using SQS/SNS/Kinesis/MSK (or Kafka) and workflow orchestration using Step Functions.
  • Demonstrated proficiency with CI/CD and Infrastructure as Code using Terraform/CloudFormation/CDK and Git-based pipelines (e.g., Jenkins, GitHub Actions).
  • 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
  • Advanced understanding of agile delivery practices, including CI/CD, application resiliency, and secure-by-design engineering.
  • Strong communication skills and engineering judgment, with the ability to own services end-to-end in a regulated, financial services environment.
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