Lead Software Engineer Agentic AI, JavaPython

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

As a Lead Software Engineer at JPMorganChase within the Commercial and Investment Banks Engineering and Architecture Team youare 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 firms 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

• Lead a local team of software engineers and applied AI/ML practitioners driving accountability and engagement within a global organization.

• Collaborate with product and business teams to set technical vision and execute strategic roadmaps for AI-driven software solutions.
• Translate business requirements into robust software and AI/ML specifications define milestones and ensure timely delivery using Agile methodologies.
• Architect design and develop secure high-quality production software systems using Java or Python integrating AI/ML techniques such as LLMs Generative AI and coding assistants
• Identify opportunities to automate and remediate recurring issues improving overall system reliability.

• Design experiments implement algorithms validate results and productionize performant scalable and trustworthy AI/ML solutions.

• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality delivery speed and operational outcomes (e.g. AI-assisted code review/refactoring test strategy acceleration incident/root-cause analysis support) while establishing consistent validation standards (secure coding peer review automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain including enterprise-authorized AI-assisted development and automation capabilities to improve the value realized by automation.

Required qualifications capabilities and skills

• Formal training or certification in software engineering concepts and 5 years applied experience
• Familiarity with agentic workflows and frameworks (e.g. LangChain LangGraph Auto-GPT)
• Advanced proficiency in Java or Python for software system development; strong grasp of software engineering best practices system design application development testing and operational stability
• Experience integrating AI/ML techniques into software systems including familiarity with LLMs Generative AI NLP RAG AI evals and coding assistants
• Managing and mentoring software engineering or AI/ML teams with experience as a hands-on practitioner delivering production-grade solutions
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g. for coding code review test acceleration troubleshooting) with the ability to set team expectations for validating AI outputs for correctness performance and security
• Strong understanding of responsible AI use in engineering workflows including data sensitivity considerations secure handling of inputs/outputs and adherence to resiliency and security expectations; experience coaching engineers on safe compliant adoption within delivery practices
• Good understanding of data structures algorithms and practical machine learning frameworks (e.g. TensorFlow PyTorch Scikit-Learn)
• Proficiency in automation continuous delivery (CI/CD) and cloud-native development (preferably AWS)

• Hands-on practical experience delivering system design application development testing and operational stability

• Experience working at code level with advanced AI/ML business applications (e.g. LLMs Generative AI NLP)
• AWS Certifications (Solution Architect Associate or Professional) are advantageous
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience