JPMorgan Product Manager Planning Analysis 

United States, New York, New York 

472130314

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
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Candidates should have already undergone AI transformation and possess exposure to building AI solutions.
• Practical experience with public cloud services, specifically AWS, is essential. This includes working with ECS, Lambda, Aurora PostgreSQL, SQS, SNS, EventBridge, Step Functions, and Terraform.
• Advanced in one or more programming language(s)
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• In-depth knowledge of the financial services industry and their IT systems
• Practical cloud native experience

• System Understanding and Automation: Ability to understand current systems and identify use cases and opportunities to automate processes using LLMs and agentic AI frameworks. Skilled in evaluating existing workflows and proposing AI-driven enhancements for efficiency and innovation.
• Experience with Large Language Models (LLMs): Demonstrated experience in developing, fine-tuning, and deploying large language models such as GPT, BERT, or similar architectures. Familiarity with the latest advancements in LLMs and their applications in various AI-driven solutions.
• Model Context Protocol (MCP): Proven experience in implementing Model Context Protocols to enhance the interaction and integration of AI models within complex systems. Ability to design and optimize MCP for improved model performance and contextual understanding.
• Agentic AI Development: Expertise in developing agentic AI systems capable of autonomous decision-making, task execution, and interaction with other AI agents. Experience in creating AI agents that exhibit goal-oriented behavior and adaptability in dynamic environments.