Lead Software Engineer Java

JPMorganChase; Bengaluru; Hybrid; INR 2,500,000 - 4,500,000; Full time

Job summary

JPMorgan Chase seeks an experienced software engineer to join an agile team delivering secure, scalable market-leading technology products. You will drive significant business impact using deep technical expertise across Java, Spring Boot, AWS services, and AI-assisted development practices.

Key focus areas include guiding secure coding, implementing AI-assisted tooling governance, and ensuring robust data handling and security across the SDLC in a fast-paced environment.

Qualifications

• Formal training or certification on software engineering concepts and 6+ years applied experience.
• Hands-on experience in system design, application development, testing, and support.
• Proficient in coding in Java (OOPS, Streams, Lambdas, Exceptions).
• Strong knowledge of Spring Boot, REST API principles, and AWS services (Step Functions, Lambda, S3, ECS/EKS, API Gateway).
• Experience with AI-assisted software development tools and governance.
• Experience leading adoption of enterprise AI tools across engineering teams.
• Understanding of responsible AI use in engineering workflows.
• Working knowledge of AWS AI/ML and NLP services such as SageMaker, Bedrock, Comprehend, Textract.
• Experience with Elasticsearch for large-scale search, indexing, analytics.
• Solid understanding of relational databases, SQL, CI/CD, and agile practices.

Responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes with measurable validation standards
• Applies knowledge of tools within the SDLC toolchain, including AI-assisted development and automation capabilities, to improve value realized by automation at scale
• Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes
• Applies knowledge of tools within the SDLC toolchain to improve the value realized by automation and support capacity unlock initiatives
• Drives decisions that influence product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Skills

Java

Spring Boot

REST APIs

AWS

AI in software

CI/CD

SQL

Agile

Leadership

Education

Software engineering certification

Tools

Elasticsearch

SageMaker

Bedrock

Textract

OpenSearch

Kinesis

AWS Lambda

S3

ECS/EKS

Job description

Job Description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

Job Description

Be 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job Responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• 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.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and 6+ years applied experience
• Hands-on experience in system design, application development, testing, and support
• Proficient in coding in Java (e.g., OOPS, Collections. Streams, Lambdas, Collections, Exception handling)
• Strong knowledge of Spring Boot framework, REST API design principles and best practices Hands-on experience with **AWS services** including Step Functions, Lambda, S3, ECS/EKS, and API Gateway, with a focus on cloud migration readiness.
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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.
• 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.
• 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 senior engineers/leads on compliant usage patterns and controls.
• Working knowledge of **AWS AI/ML and NLP services** such as Amazon SageMaker, Bedrock, Comprehend, and Textract
• Experience with **Elasticsearch** for large-scale search, indexing, and analytics
• Solid understanding of relational databases, SQL, CI/CD pipelines, and agile development practices.

Preferred qualifications, capabilities, and skills

• Familiarity with AI/ML concepts including embeddings (Word2Vec, BERT), NLP techniques, vector search, and retrieval-augmented generation (RAG) patterns.
• Exposure to additional AWS data services such as **OpenSearch, Glue, Athena, or Kinesis**.