As a Software Engineer III at JPMorganChase within the Sales Assistant Technology team you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. 

You'll be part of the team to build Markets Sales AI Platform to on-board agentic workflows into our system in a federated way, turning frontier GenAI capabilities into reliable, high-leverage agentic systems that transform how we respond to inbound client requests.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Build agentic platform with UI, orchestration, routing, memory, training ground and evaluations frameworks end-to-end: design, prototype, and productionize multi-step LLM agents that retrieve context and generate accurate, well-structured responses
• Drive applied AI by evaluating emerging techniques (tool use, planning, retrieval, evaluation frameworks, fine-tuning, prompt optimization) and integrating the best into production
• Improve quality systematically via evals, error analysis, and feedback loops that convert subjective issues into measurable fixes
• Partner cross-functionally with quant research,  product, and engineering to understand their agents and provide solutions on-board on to our platform in a federated way.
• Build and maintain production-grade code and systems that are observable, robust, and scalable
• Contribute to technical direction and standards for agent design, evaluation, and safe deployment
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Required qualifications, capabilities, and skills

• Formal training or certification on infrastructure engineering concepts and 3+ years applied experience 
• Degree in Computer Science, Data Science, Machine Learning or related field or equivalent experience
• Strong coding skills (Python) and comfort owning production code
• Hands-on experience in AWS, ECS, Bedrock, OpenSearch, Vector dbs and PostGres 
• Familiarity with evaluation frameworks, LLM observability, or fine-tuning open-weight models
• Hands-on experience building with LLMs (agent frameworks, tool use, RAG, prompt engineering, evals)
• Strong understanding of modern GenAI capabilities, failure modes, and practical mitigation strategies
• Strong ownership and drive mindset with a focus on improving what’s broken with clear design principles

Preferred qualifications, capabilities, and skills

• OpenSearch, Vector dbs and Postgres nice to have