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Manager of Software Engineering

up to ₹6500k/year Hyderabad, Telangana, India Full-time
Engineering ManagerJava DeveloperFull Stack Java DeveloperFull Stack Node.js DeveloperDevOps EngineerPrincipal EngineerNode.js DeveloperTechnical ArchitectCloud EngineerStaff Engineer

hackajob is partnering with JPMorganChase to fill this position. Create a free profile and Archer will check you against this role and every other live role, showing you exactly where you match.

JOB DESCRIPTION

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team.

As a Manager of Software Engineering at JPMorgan Chase within Consumer and community banking technology team, 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 delivering critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives

Job Responsibilities

  • Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems. 

  • Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.

  • Use domain modeling techniques to build best-in-class business products, structuring software for clarity, testability, and evolution.

  • Develops secure high-quality production code, and reviews and debugs code written by others.

  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.

  • Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.

  • Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
  • 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 and support capacity unlock initiatives.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years of hands-on experience in software engineering, including system design, application development, testing, and operational support.

  • Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular).

  • Demonstrated ability to independently solve design and functionality challenges with minimal supervision.

  • Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.

  • Hands-on experience designing and building scalable applications using SQL and NoSQL databases.

  • Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle.

  • Understanding of application resiliency

  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security. 

  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.). 

  • Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.

  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.

Preferred qualifications, capabilities, and skills

  • Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.

  • Strong problem-solving, analytical, and communication skills.

  • Ability to drive broader impact by sharing and contributing best practices.

  • Experience in the banking domain.

  • AWS certification.

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