Lead Software Engineer -GenAI , Java full stack

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Consumer and community banking- Architecture & Engineering , you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities

• 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
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s) including Java/ Python (fastAPI), Microservices, API, LLM, and AWS (EC2, ECS, EKS, Lambda, SQS, SNS, RDS Aurora Oracle & Postgres, DynamoDB, S3)
• Develop innovative AI/ML solutions and agentic systems leveraging LLM on public cloud with modern standards, specifically with AWS, and AI Agentic frameworks
• Develop and implement state-of-the-art GenAI services leveraging Azure OpenAI models and AWS Bedrock service.
• Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray) & Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints
• Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints & Knowledge in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models
• Understanding of large language model (LLM) approaches, such as Retrieval-Augmented Generation (RAG) and agent-based models, is essential.

• Real-time model serving experience with Seldon, Ray, or AWS SM is a plus.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG).
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
• Good understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs is a plus.