Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Sr Lead Software Engineer at JPMorgan Chase within the Community and Consumer Banking (CCB) - Engineering Tools & Productivity (ET&P) team, you will play a pivotal role in an agile team dedicated to enhancing, building, and delivering market-leading technology products that are secure, stable, and scalable.
You will be a core technical contributor, designing and implementing innovative Agentic AI solutions across the Product Development Life Cycle (PDLC), leveraging advanced AI/ML techniques to boost developer efficiency and accelerate developer efficiency toolchain adoption, resulting in faster product feature rollouts with enhanced stability and quality.
Job responsibilities
Required qualifications, capabilities, and skills
Solid background in Generative/Agentic AI personalization and hands-on expertise in applying machine learning and deep learning methods across PDLC phases
Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
Experience with scalable model training and strong written and spoken communication skills to effectively convey technical concepts and results to both technical and business audiences
Extensive practical experience with cloud-native applications, Object-Oriented principles, microservice-driven architecture, REST architectural style, and RESTful APIs
Hands-on expertise in one or more modern programming languages and cloud platforms like Java/JavaScript/Python on AWS/Pivotal Cloud Foundry/GCP/Azure using Kubernetes
Extensive experience with machine learning and deep learning toolkits (., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
Curious, detail-oriented, and motivated by complex technical problems
Preferred qualifications, capabilities, and skills
Strong research, investigation, presentation and evaluation skills.
In-depth knowledge of the financial services industry and their IT systems
Expertise in training and fine-tuning large language models (LLMs) and embedding models, including advanced knowledge in the areas of LLM operations (LLM Ops) and AI operations (AIOps)