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 Commercial & Investment Bank, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of 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 problemsCreates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systemsProduces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code developmentGathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systemsProactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architectureContributes to software engineering communities of practice and events that explore new and emerging technologiesAdds to 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 experienceHands-on practical experience in ML/GenAI based system design, application development, testing, and operational stabilityExperience in developing, debugging, and maintaining code in a large corporate environment with modern programming language Python along with database querying languages SQL.Hands-on experience on ML and GenAI based system development.Exposure to ML Techniques like Supervised and Unsupervised Learning methodologies etc.Experience across the whole Software Development Life Cycle especially on Data Science.Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security.

Preferred qualifications, capabilities, and skills

Exposure to cloud technologies like AWS/Azure/GCP Exposure to LLM models like ChatGPT, Google Bard etc.Exposure to Langchain, RAG and Fine Tuning of the LLM Models.Exposure to PySpark and Databricks for Data pipeline creation.