Software Engineer III - Python, AWS

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 Asset & Wealth Management, 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

• Involves in building and operating highly sophisticated LLM driven applications.
• Partners directly with other technology teams on LLM projects to advise and assist as needed.
• Collaborates with Data Science, Cybersecurity to deliver state of the art ML products.
• Collaborates with Devops engineers to plan and deploy data storage and processing systems,
• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Develops secure high-quality production code, and reviews and debugs code written by others.
• Stays abreast of the latest advancements in AI technologies, and drive their integration into our operations.

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Advanced python programming skills.
  
  Proven experience in building and operating scalable ML-driven products.
• Azure and/or AWS Certifications ( Architect, Big Data, AI/ML ) .
• Hands on experience in Azure and AWS.. Proficiency with cloud technologies like Kubernetes, Airflow.
• Experience working in a highly regulated environment.
  
  Proven ability to iterate quickly.
• Proficient in all aspects of the Software Development Life Cycle.

• Experience with financial data and data science.
• Experience in developing AI solutions using agentic frameworks.
  
  Experience fine-tuning LLMs with advanced techniques to enhance performance.
• Experience with prompt optimisation to improve the effectiveness of AI applications.
• Demonstrated ability to design and implement robust AI application architectures.