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

As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate Sector, AI/ML Data Platforms Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading and cutting-edge technology products in a secure, stable, and scalable way. In this role you will work with technology which includes AI/ML Platform Solutions using LLMs, public cloud and modern standards and patterns. 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

Develops cutting edge AI/ML Platform solutions using LLMs, public cloud and modern standards and patterns. Develops and implements state-of-the-art generative AI services leveraging Azure Open AI models and AWS Bedrock service. Develops solutions using AWS Cloud Services for compute, storage, databases, and security and Azure Services Develops advanced monitoring and management tools for high reliability and scalability. Architect and implement distributed ML infrastructure, including inference, training, scheduling, orchestration, and storage. Optimizes system performance by identifying and resolving inefficiencies and bottlenecks. Works closely with the Product team to design, build and deliver capabilities in agile sprints. Collaborates with cross-functional teams, including data scientists, software engineers, and designers, to integrate generative AI into various applications and products.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience. Strong coding skills and experience in developing large-scale ML systems. Deep expertise in AWS / GCP and Kubernetes ecosystem, including EKS, Helm, and custom operators. Hands-on experience with ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn). Hands-on experience working on AWS Cloud Based applications development using EC2, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, and Kinesis.  Deep expertise across application, data, security, and infrastructure disciplines Experience in setting up public cloud infrastructure using TerraForm. Experience working containerized services on Kubernetes or ECS Experience with Python, Java, and REST APIs. Solid understanding of improving and debugging backend performance bottlenecks. Experience with application production readiness, production monitoring, and production issue triaging

Preferred qualifications, capabilities, and skills

Knowledge of AWS Sagemaker and data analytics tools will be a plus.    Knowledge on new model architectures using optimizations like quantization and pruning. Ability to adapt to new technologies and learn quickly in a fast-paced environment Knowledge or experience with working on Azure