As a Software Engineer III, you'll design and implement secure AI applications, analyze data for improvements, and develop software solutions in a collaborative agile environment.
Job Description
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Consumer and Community Banking - Wealth Management, you will be a seasoned member of an agile team, tasked with designing and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. You will be responsible for implementing critical technology solutions across multiple technical domains, supporting various business functions to achieve the firm's business objectives.
Job responsibilities
Required qualifications, capabilities, and skills
Preferred qualifications, capabilities, and skills
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
As a Software Engineer III at JPMorgan Chase within the Consumer and Community Banking - Wealth Management, you will be a seasoned member of an agile team, tasked with designing and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. You will be responsible for implementing critical technology solutions across multiple technical domains, supporting various business functions to achieve the firm's business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code, maintaining algorithms that integrate seamlessly with generative AI systems and other appropriate technologies.
- Produces architecture and design artifacts for complex generative AI applications, ensuring design constraints are met by software code development.
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets to continuously improve generative AI applications and systems.
- Proactively identifies hidden problems and patterns in data, using these insights to drive improvements in coding hygiene and system architecture specific to generative AI.
- Contributes to software engineering communities of practice and events that explore new and emerging generative AI technologies.
- Fosters a team culture of diversity, equity, inclusion, and respect.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 3+ years applied experience.
- Proficient in coding in one or more languages, with a strong emphasis on Python and AI/ML frameworks.
- Experience in developing, debugging, and maintaining code in a large corporate environment, utilizing modern programming languages and database querying languages.
- Comprehensive knowledge of the Software Development Life Cycle, with a focus on generative AI applications.
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, particularly in the context of AI/ML.
- Demonstrated knowledge of software applications and technical processes within technical disciplines such as cloud computing, artificial intelligence, machine learning, and mobile technologies.
- Expertise in AWS and GenAI/ML technologies.
Preferred qualifications, capabilities, and skills
- Experience with AI model optimization and performance tuning to ensure efficient and scalable AI solutions.
- Familiarity with data engineering practices to support AI model training and deployment.
- Ability to collaborate with cross-functional teams to integrate generative AI solutions into broader business processes and applications.
- Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.
- Experience with AI/ML libraries and tools such as TensorFlow, PyTorch, Scikit-learn, and Keras.
Top Skills
AI
AWS
Keras
Ml
Python
PyTorch
Scikit-Learn
TensorFlow
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