Location: Bengaluru, Karnataka, India

As a Software Engineer II at JPMorgan Chase within the Infrastructure Platforms International, you are part of an agile team that enhances, designs, and delivers the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. You execute software solutions through design, development, and technical troubleshooting of multiple components within a technical product, application, or system. If you are passionate about developing innovative applications using Python and LLMs, we encourage you to apply and join our dynamic team!

Job Responsibilities:

• Develop and maintain Python-based web applications utilizing Large Language Models (LLMs).
• Perform data vectorization and fine-tuning of LLMs to enhance performance and accuracy.
• Orchestrate LLM workflows using frameworks such as Langchain, Langraph, or LlamaIndex.
• Build and deploy Python microservices for scalable application architecture.
• Integrate and connect to diverse data sources, including unstructured databases like PostgreSQL.
• Implement LLM-based data vectorization techniques and ensure efficient storage in PostgreSQL.
• Collaborate with cross-functional teams to gather requirements and deliver high-quality solutions.

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on software engineering concepts and 2+ years applied experience   

• Proficiency in Python development with a strong understanding of web application frameworks.
• Experience with Large Language Models (LLMs) and their fine-tuning.
• Familiarity with data vectorization techniques and their applications.
• Experience with orchestrating LLM workflows using frameworks like Langchain, LLamaIndex, or Langraph.
• Strong knowledge of building and deploying Python microservices.
• Proficient in connecting and querying PostgreSQL.
• Excellent problem-solving skills and ability to work independently and collaboratively.
   

Preferred Qualifications, Capabilities, and Skills:

• Machine Learning with Python (Clustering, Classification).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying applications.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes).
• Knowledge of front-end technologies (e.g., HTML, CSS, JavaScript) is a plus.