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Lead Software Engineer AI/ML Solutions

في الامس 2025/07/13
خدمات الدعم التجاري الأخرى
أنشئ تنبيهًا وظيفيًا للوظائف المشابهة

الوصف الوظيفي

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 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 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 the Gen 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 Python, 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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