Lead Software Engineer - AI ML

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead AI/ML Product Manager & Engineer at JPMorgan Chase within the Payments Technology team, you will play a crucial role in our agile team, designing and delivering secure, stable, and high-quality ML/GenAI technology products. You will promote the product vision and strategy while implementing critical AI technology solutions across technical domains and business functions, supporting the firm's business objectives.

Job Responsibilities

• Defines product vision, strategy, and roadmap for AI/ML initiatives in Payments Technology.
• Executes software solutions, design, development, and technical troubleshooting, thinking beyond routine approaches to build solutions or break down technical problems.
• Creates secure and high-quality production-level code and maintain algorithms that run synchronously with appropriate systems.
• Produces architecture and design artifacts for complex applications, ensuring design constraints are met by software code development.
• Gathers, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to drive continuous improvement of software applications and systems.
• Identifies hidden problems and patterns in data, using insights to drive improvements in coding hygiene and system architecture.
• Collaborates with engineering, data science, and business stakeholders to prioritize features and deliver solutions.
• Manages product lifecycle from ideation to launch and post-launch optimization.
• Ensures compliance with data privacy, security, and regulatory requirements.
• Contributes to software engineering communities of practice and events that explore new and emerging technologies.
• Fosters a team culture of diversity, equity, inclusion, and respect.

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Hands-on practical experience in ML/GenAI-based system design, application development, testing, and operational stability.
• Experience developing, debugging, and maintaining code in a large corporate environment using modern programming languages (Python) and database querying languages (SQL).
• Experience with ML techniques such as supervised and unsupervised learning methodologies, and exposure to LLMs.
• Experience across the full Software Development Life Cycle, especially in Data Science.
• Experience of cloud technologies (AWS, Azure, GCP).
• Experience with Langchain, Retrieval-Augmented Generation (RAG), and fine-tuning LLM models. Knowledge of generative AI, NLP, or computer vision
• Experience in agile methodologies such as CI/CD, application resiliency, and security.
• Experience in PySpark and Databricks for data pipeline creation.

• Experience in financial services or regulated industries.
• Familiarity with LLM models (ChatGPT, Google Bard, etc.).
• Excellent communication, leadership, and stakeholder management skills.
• Experience with agile methodologies and product development best practices.