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Lead Software Engineer - Full Stack-Generative AI

Job in Plano, Collin County, Texas, 75086, USA
Listing for: Testing Site - JPMC
Full Time position
Listed on 2026-10-18
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR
Job Description & How to Apply Below

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 specializing in Full Stack Engineering and Generative AI at JPMorgan Chase within the Asset and Wealth Management division, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You leverage advanced skills in full stack development and artificial intelligence to consistently challenge the status quo, innovate for business impact, contribute to the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances.

This role focuses on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions.

Job responsibilities:
  • Lead the design and implementation of AI-driven solutions to optimize and modernize business processes.
  • Develop solutions using advanced proficiency in large language models (LLMs), agentic frameworks, and related techniques, integrating these with backend (Java, Python) and frontend (React) systems.
  • Build and maintain high-quality software using Java, Spring Boot, Microservices, and React Micro frontends.
  • Design and implement cloud-based applications on AWS and Private Cloud environments.
  • Implement evaluation and feedback loops for Generative AI and ML pipelines.
  • Provide technical guidance on the feasibility and business need for AI/ML use cases; establish and promote best practices in Generative and Agentic AI.
  • Collaborate with firm-wide AI/ML and engineering stakeholders, as well as across business, product, and technology teams, to manage stakeholder relationships and drive alignment.
  • Translate complex technical issues, trends, and approaches to leadership to enable strategic, well-informed decisions about technology advancements.
  • Work with team members to product ionize end-to-end AI/ML solutions that address impactful business needs.
  • Champion the firm's culture of equity, opportunity, inclusion, and respect.
Required qualifications, capabilities, and skills:
  • Formal training or certification in Software Engineering, Data Science, Artificial Intelligence, or Computer Science and 5+ years of applied experience in software engineering and AI.
  • 8+ years of software development experience.
  • Proven expertise in Java, Spring Boot, Microservices, React Micro frontends, AWS, and Dev Ops.
  • Proficient in Python with hands-on experience developing production AI/ML solutions.
  • Familiarity with agentic workflows and frameworks (e.g., Lang Chain, Lang Graph, CrewAI).
  • Experience with Large Language Models, Retrieval-Augmented Generation (RAG), Vector Store, and Model Context Protocol (MCP).
  • Ability to bring experimental results into production by collaborating with engineering teams and integrating with cloud platforms.
  • Strong problem-solving skills and ability to work independently.
  • Excellent communication skills and demonstrated experience leading engineering teams and managing projects.
  • Familiarity with CI/CD pipelines and tools such as Jenkins and Git Hub Actions.
  • Ability to work on system design from ideation through completion with limited supervision.
Preferred qualifications, capabilities, and skills:
  • Cloud certification (AWS, GCP, Azure).
  • Solid understanding of Data Analysis and Machine Learning techniques.
  • Experience with machine learning frameworks such as Tensor Flow, Keras, PyTorch, Scikit-learn, Num Py.
  • Understanding of asset and wealth management business processes.
  • Understanding of SQL and Kafka.
  • Passion for detail and follow-through, and a strong team player.
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