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Salary
$35k – $92k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff
Overview
Company
Impact
Profile match
JPMorgan Chase & Co. is a leading global financial services firm and the largest banking institution in the United States by assets. Headquartered in New York City, the company offers a comprehensive range of financial solutions, including investment banking, asset management, treasury services, and commercial banking. Through its widely recognized consumer division, Chase, it delivers retail banking, credit card, and mortgage services to tens of millions of households across the globe.

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

As a Senior Lead Software Engineer at JPMorganChase within the CORPORATE TECHNOLOGY - Risk Technology 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. 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.
  • 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
  • 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**.
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