Senior Lead Software Engineer- Java/Python/ AI Solutions

hackajob** is collaborating with **J.P. Morgan** to connect them with exceptional professionals for this role. **Job Description 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 Senior Lead Software Engineer- Java/Python/ AI Solutions at JPMorganChase within the Asset and Wealth Management Technology team, 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

This is a rare opportunity to help shape the future of our Private Bank. With the sponsorship from the CEO and the heads of the business, our goal is to create an Agentic Private Bank - reimagining the entire process from start to finish, rethinking the operating model including organizational structures and developing AI agents equipped with the latest tools and technologies to fundamentally reshape how we perform this business.

Join our dynamic team of innovators and technologists, where your mission will be to revolutionize how the Bank services and advises clients, deepen client engagements, and drive process transformation. Our culture thrives on experimentation, continuous improvement, and learning. You will work in a collaborative, trusting, and intellectually stimulating environmentâone that values diversity of thought and fosters creative solutions that serve the best interests of our global clientele.

Job Responsibilities

• Lead the end-to-end design, development, and deployment of client-facing Generative AI and Agentic AI solutions that enhance automation, personalization, and decision-making for external clients.
• Architect and implement prompt-based models on Large Language Models (LLMs) for NLP tasks tailored to financial services use cases such as document summarization, intelligent search, conversational interfaces, and advisory support.
• Design and build autonomous agentic AI workflows capable of multi-step reasoning, tool use, and task execution with appropriate human-in-the-loop guardrails aligned with emerging enterprise patterns such as OpenAI Frontier and Anthropic Claude Cowork
• Implement Model Context Protocol (MCP) integrations to enable AI agents to securely connect to and interact with external data sources, APIs, and enterprise tools in real time.
• Build and maintain scalable data pipelines and data processing workflows for both structured and unstructured data, leveraging cloud services to support LLM-based features and real-time client interactions.
• Design and develop robust APIs and microservices to integrate AI/LLM models into client-facing platforms, ensuring seamless, low-latency experiences.
• Develop secure, high-quality, production-grade code that powers client-facing applications, ensuring reliability, performance, and compliance with financial industry standards.
• Produce architecture and design artifacts for complex, distributed applications while ensuring design constraints, including latency, throughput, and regulatory requirements, are met and implement observability, monitoring, and feedback loops for agentic AI systems to track agent behavior, detect hallucinations, and ensure reliability in high-stakes financial applications
• Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse datasets to inform product improvements, monitor model performance, and enhance client outcomes and proactively identify hidden problems and patterns in data and system behavior, using these insights to drive improvements to code quality, system resilience, and client experience.
• Partner closely with product, design, and business stakeholders to translate client needs and business requirements into scalable AI-driven technical solutions.
• Ensure all client-facing solutions adhere to strict security, privacy, and regulatory standards applicable to the financial services industry, including data protection, model governance, and responsible AI practices, particularly as regulators increase scrutiny of autonomous AI agents in financial services.

Required Qualifications, Capabilities, And Skills

• Formal training or cert…