Lead AI Engineer for Sales Assistant Platform Technology - Lead Software Engineer

JPMorgan Chase; Jersey City (NJ); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorganChase in Jersey City, NJ is seeking a Lead Software Engineer to drive key components of Markets Sales AI Platform and onboard agentic workflows in a federated, scalable manner. You will ship production-grade code and own end-to-end delivery with a focus on secure and observable systems.

You’ll lead design, integration, and evaluation of LLM-based solutions, partnering with Quant Research, Product, and Engineering to turn frontier GenAI capabilities into reliable, high-leverage agentic

Qualifications

• Formal training or certification in software engineering concepts with 5+ years of applied experience
• Degree in Computer Science, Data Science, Machine Learning or related field
• Strong coding skills (Python) and comfort owning production code
• Hands-on experience in AWS, ECS, Bedrock
• Agentic development tool kit example Google ADK must have
• 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
• Experience working in a fast pace environment

Responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Drive/Build/Own 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
• 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.
• 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

Skills

Python programming

Production-grade code ownership

Fast-paced environment adaptability

Strong ownership mindset

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

ECS

Bedrock

Google ADK

Job description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Lead Software Engineer at JPMorganChase within the Sales Assistant 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. 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 firm's business objectives.

You'll be part of the team to drive, own and build key components of 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. This is a hands-on role for someone who thrives on ambiguity, ships quickly, and is energized by hard technical challenges.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Drive/Build/Own 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
• 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.
• 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

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Degree in Computer Science, Data Science, Machine Learning or related field or related experience
• Strong coding skills (Python) and comfort owning production code
• Hands-on experience in AWS, ECS, Bedrock.
• Agentic development tool kit example Google ADK must have
• 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
• Experience working in a fast pace environment

Preferred qualifications, capabilities, and skills

• OpenSearch, Vector dbs and Postgres nice to have