Lead Software Engineer - Java, AWS, Golang

JP Morgan Services India Pvt Ltd; Bengaluru; On-site; INR 6,000,000 - 9,500,000; Full time

Job summary

JPMorgan Chase in Bengaluru seeks a Lead Software Engineer to define and deliver trusted market-leading technology products. You will play a core role in an agile team, delivering secure, scalable software while driving AI-assisted engineering practices across the SDLC.

Responsibilities include building secure production code, reviewing peers, and guiding architectural decisions with external vendors and internal teams.

Qualifications

• Formal training or certification on software engineering concepts and 8+ years' applied experience.

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

Skills

Java

Go Lang

Kubernetes

AWS

AI-assisted development

CI/CD

Agile

SQL/NoSQL

Tools

Kubernetes (AWS EKS)

Job description

Lead Software Engineer - Java, AWS, golang

Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers As a Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank, 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

• 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 8+ years' applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficient hands-on experience in Java, Go-Lang programming languages using micro-services architecture
• Strong database fundamentals across both SQL and NoSQL, including data modeling and design patterns, indexing strategies, query optimization, and transaction management
• Hands-on experience deploying and operating workloads in private Kubernetes environments and within the AWS Kubernetes ecosystem (e.g., EKS), including Deployments, Services, Ingress, configuration and secrets management, and autoscaling
• 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
• In-depth knowledge of the financial services industry and their IT systems

Preferred qualifications, capabilities, and skills

• Messaging/streaming systems (Kafka/SQS/SNS/RabbitMQ) and event-driven architectures
• Experience with service mesh / advanced traffic management (e.g., Istio/Linkerd) and API gateways
• Infrastructure-as-Code exposure (Terraform/CloudFormation) and environment automation