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 Corporate Technology  Consumer and Community Banking Risk Technology team 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 problemsWork with product managers, data scientists, ML engineers, and other stakeholders to understand requirements.Develop API/services for model deployment, ensuring scalability, reliability, and efficiency.Build applications to automate manual steps in MLOPs pipeline.Execute POC and for innovative ideas to solve complex business problemsStay informed about the latest trends and advancements in the latest LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.Adds 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 of applied experience.Proficient in programming languages like Python for model development, Python for BigData i.e. Pyspark, Spark SQL on EMR experienceweb application/ APIs need experience with AWS lambda, cloud gateway etc.Experimentation, and integration with OpenAI API.Experience is building API and restful services using Flask/Django/FastAPISolid understanding of agile methodologies such as CI/CD, Application Resiliency, and SecurityExperience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.Understanding of fundamentals of machine learning and LLMs.Experience in applied AI/ML engineering, with a track record of deploying business critical machine learning models in production.

 

Preferred qualifications, capabilities, and skills

Familiarity with modern front-end technologiesFamiliarity with the financial services industries