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JPMorgan AML Reputation Risk Escalation - Associate 
Singapore 
556515893

Yesterday

As a Lead Software Engineer at JPMorgan Chase within the Corporate Investment Bank, Markets Research Technology Team, you will play a crucial role in an agile team, focusing on the design and delivery of secure, stable, and scalable market-leading technology products. Your responsibilities will encompass implementing essential technology solutions across various technical domains to support the firm's business goals. You will participate in innovative projects, including LLM and GenerativeAI solutions, and aid in the industrialization of AI/ML models at a production scale. This position is a hands-on team member contributor engineering role.

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 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
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Adds to the team culture of diversity, opportunity, inclusion, and respect
  • Designs and implements hands-on solutions while providing technical leadership and mentorship to more junior team members

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and proficient advanced experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in Python software engineering
  • Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., Data engineering, ML engineering, Cloud)
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Practical cloud native experience
  • Practical experience with Kubernetes, EKS, Docker, Terraform, MLOps

Preferred qualifications, capabilities, and skills

  • Experience developing large-scale Cloud-native data/AI/ML engineering solutions in large corporate environments
  • Prior experience collaborating with data scientists, productionizing POCs to industrial scalable solutions
  • AWS clod native experience
  • Experience with data science/ML modelling
  • Familiarity with modern LLM technologies, Vector databases (e.g., OpenSearch), and Knowledge Graph