Lead Software Engineer - AIML Solutions

apartmentJP Morgan Chase & Co. placeBangalore calendar_month 

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Consumer & community Banking- Data Technology youare 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 break down technical problems
  • 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
  • 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
  • Enable theGen AI platform and implement the Gen AI Use cases ,LLM fine tuning and multi agent orchestration
  • Communicate technical concepts and solutions effectively across all levels of the organization.
  • Lead the design and development of our AI/ML platform, ensuring robustness, scalability, and high performance.
Required Qualifications, Capabilities, and Skills
  • Formal training or certification on software engineering concepts and 5+ years of applied experience
  • Extensive practical experience with AWS cloud services, including EKS, EMR, ECS, and DynamoDB.
  • Experience in DataBricks ML lifecycle development.
  • Advanced knowledge in software engineering, AI/ML, machine learning operations (MLOps), and data governance.
  • Demonstrated prior experience in leading complex projects, including system design, testing, and ensuring operational stability.
  • Expertise in computer science, computer engineering, mathematics, or a related technical field.
  • Understanding of large language model (LLM) approaches, such as Retrieval-Augmented Generation (RAG)
  • Real-time model serving experience with Seldon, Ray,
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