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Senior Lead Software Engineer- Java Backend

JPMorgan Chase
Mumbai, IND
Full-time
Senior · 5+ years experience
Onsite
Discovered 1 weeks ago
awsgitjavajenkinsspring-boot

Full Job Posting

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 on software engineering concepts and 5+ years applied experience Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Strong hands-on experience building modern applications Java + Spring Boot (backend) with microservices.
  • DevOps Fundamentals: Strong working knowledge of Git and CI/CD tools such as Jenkins.
  • AWS / Cloud Skills: Hands-on experience with AWS (building/deploying cloud-native services, working knowledge of core services and cloud security basics).
  • Strong Communication & Problem Solving: Clear communicator with strong analytical skills, able to collaborate effectively across Product, Architects and QA.
  • 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
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability

Preferred qualifications, capabilities, and skills

  • System Architecture: Designing and implementing autonomous agent architectures, including cognitive, memory, and planning capabilities.
  • Agentic Workflows: Develop end-to-end multi-agent systems where AI agents collaborate to perform tasks such as comprehensive system development, rigorous testing, and thorough validation to ensure reliability and performance. React (frontend)
  • Tool Integration: Integrating LLMs with external APIs, databases, and software tools to allow agents to act independently.
  • Governance & Safety: Establishing guardrails and security protocols to ensure autonomous actions align with organizational policies.
  • Evaluation & Optimization: Debugging, monitoring, and evaluating agent performance (AgentOps) to optimize for accuracy and reliability.

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