Posted 17 days ago
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Senior technical leader within Asset and Wealth Management Technology at JPMorgan Chase responsible for designing, building, and deploying GenAI and agentic AI solutions to drive automation and decision-making. The role leads development of prompt-based LLM models, prompt engineering research, data pipelines for structured and unstructured data, and production MLOps while collaborating with cross-functional teams and senior stakeholders. Hands-on responsibilities include Python development, PyTorch/TensorFlow work, LLM orchestration, API integration, and cloud-based AI/ML deployment.
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Location: Bengaluru, Karnataka, India
Your opportunity to make a real impact and shape the future of financial services is waiting for you. Let’s push the boundaries of what's possible together
As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will 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 will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead 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 will focus 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 development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain.Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.Communicate effectively with both technical and non-technical stakeholders, including senior leadership.Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.Develop and maintain tools and frameworks for prompt-based model training, evaluation, and optimization.Analyze and interpret data to evaluate model performance and identify areas of improvement.Required qualifications, capabilities, and skills:
- Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.Hands-on experience in building Agentic AI solutions.Familiarity with LLM orchestration and agentic AI libraries.Strong programming skills in Python with experience in PyTorch or TensorFlow.Experience building data pipelines for both structured and unstructured data processing.Experience in developing APIs and integrating NLP or LLM models into software applications.Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.Excellent problem-solving skills and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner.Basic knowledge of deployment processes, including experience with GIT and version control systems.Hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.Preferred Qualifications, Capabilities, and Skills:
- Familiarity with model fine-tuning techniques.Knowledge of financial products and services, including trading, investment, and risk management. Drive innovation and data engineering solutions, lead a technical area, and serve as a primary decision maker for your GenAI ML Team.
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Job Details
ExperiencedNo visa sponsorshipNot specified
Currency not set
City: Bengaluru
Country: India
Senior technical leader within Asset and Wealth Management Technology at JPMorgan Chase responsible for designing, building, and deploying GenAI and agentic AI solutions to drive automation and decision-making. The role leads development of prompt-based LLM models, prompt engineering research, data pipelines for structured and unstructured data, and production MLOps while collaborating with cross-functional teams and senior stakeholders. Hands-on responsibilities include Python development, PyTorch/TensorFlow work, LLM orchestration, API integration, and cloud-based AI/ML deployment.
Full Job Description
Location: Bengaluru, Karnataka, India
Your opportunity to make a real impact and shape the future of financial services is waiting for you. Let’s push the boundaries of what's possible together
As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will 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 will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead 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 will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functionsJob Responsibilities:- Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain.Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.Communicate effectively with both technical and non-technical stakeholders, including senior leadership.Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.Develop and maintain tools and frameworks for prompt-based model training, evaluation, and optimization.Analyze and interpret data to evaluate model performance and identify areas of improvement.Required qualifications, capabilities, and skills:
- Formal training or certification on Machine Learning concepts and 10+ years applied experience. In addition, 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise.Hands-on experience in building Agentic AI solutions.Familiarity with LLM orchestration and agentic AI libraries.Strong programming skills in Python with experience in PyTorch or TensorFlow.Experience building data pipelines for both structured and unstructured data processing.Experience in developing APIs and integrating NLP or LLM models into software applications.Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.Excellent problem-solving skills and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner.Basic knowledge of deployment processes, including experience with GIT and version control systems.Hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.Preferred Qualifications, Capabilities, and Skills:
- Familiarity with model fine-tuning techniques.Knowledge of financial products and services, including trading, investment, and risk management. Drive innovation and data engineering solutions, lead a technical area, and serve as a primary decision maker for your GenAI ML Team.
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