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Chase · 4 months ago

Sr Lead Software Engineer - Agentic AI solutions

1111 Polaris Pkwy, Columbus, OH, 43240, US

Full-time

Onsite

Senior Level, Lead/Staff

$171K/yr - $260K/yr

5+ years exp

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. As a Sr Lead Software Engineer, you will be a core technical contributor, designing and implementing innovative Agentic AI solutions to enhance developer efficiency and accelerate toolchain adoption in the Product Development Life Cycle.

BankingFinancial Services

Responsibilities

Utilize expertise in deep learning, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and agentic workflows to develop cutting-edge solutions that drive integration and synergy across CCB developer efficiency initiatives

Provide leadership on Agentic AI initiatives, ensuring efficient resource allocation, compliance with data regulations, and risk minimization to maximize efficiency

Lead the design and development of robust, scalable, high-performing Agentic AI solutions across PDLC, while effectively communicating technical concepts and solutions at all organizational levels

Work closely with product management and cross-functional forums (AI4Tech CoEs & CoPs) to define roadmaps and deliverables for AI-driven developer features and capabilities

Drive the adoption of best practices in software engineering, machine learning operations (MLOps), and data governance, ensuring compliance with data privacy and security regulations

Qualification

Generative/Agentic AIMachine LearningDeep LearningCloud-native ApplicationsMLOpsProgramming LanguagesModel TrainingCuriosityCommunication SkillsDetail-oriented

Required

Formal training or certification on software engineering concepts and 5+ years applied experience

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 (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)

Curious, detail-oriented, and motivated by complex technical problems

Preferred

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)