Senior Lead Software Engineer, Artificial Intelligence

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Plano, TX
Posted: 46 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $211k

$178k most similar roles pay here $244k

This listing doesn't post a salary. Most similar roles pay $184,975–$237,287.

Based on 240 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Senior Lead Software Engineer, Artificial Intelligence

Role Posting Log in to save

As a Sr Lead Software Engineer - Artificial Intelligence within the Core Processing team for Wealth Management Technology, you will design and operate an AI toolchain to accelerate mainframe modernization. You will build agentic systems that ingest legacy COBOL, JCL, DB2, and batch schedules to produce structured specifications and modern services in Kotlin/JVM. Your daily work involves building RAG pipelines, multi-agent orchestration layers, and automated verification infrastructure to ensure calculation accuracy during migration. You will manage LLMOps tasks including monitoring, cost management, and latency optimization while extending ETL and CDC pipelines. The role requires expertise in Python, Rust, or Kotlin/JVM, along with proficiency in tools like Claude Code, GitHub Copilot, and Cursor. You will solve complex technical challenges involving code translation, parity testing, and infrastructure for financial calculation systems.

Skills

LLM RAG Prompt Engineering Agentic Workflows Kotlin Java Python Rust AWS EKS ECS Kubernetes PostgreSQL Kafka COBOL JCL DB2 Airflow Temporal CDC

What you'll do

Build and operate the RAG pipelines and chunking strategies to convert legacy mainframe artifacts into structured specifications.
Design and implement multi-agent systems to translate legacy COBOL logic into modern Kotlin/JVM code.
Create automated test harnesses and parity testing frameworks to verify calculation accuracy during migration.
Develop and extend ETL, event sourcing, and change data capture pipelines for migrated workflows.
Manage LLMOps for the AI toolchain, including monitoring, cost management, and latency optimization in production.
Build reusable libraries and orchestration patterns to scale AI capabilities across multiple core processing domains.
Collaborate with domain experts to validate agent outputs and refine prompt engineering strategies.

What we're looking for

5+ years of software engineering experience shipping production systems.
2+ years of hands-on experience building LLM-based applications including agentic architectures, RAG pipelines, and prompt engineering.
Strong fundamentals in distributed systems, event-driven architectures, API design, testing practices, and cloud platforms (AWS/EKS/ECS).
Expert proficiency with AI-assisted development tools such as Claude Code, GitHub Copilot, and Cursor.
Experience with at least one of Kotlin/JVM (Java), Python, or Rust in production environments.
Demonstrated ability to operate and debug complex systems and communicate technical trade-offs to stakeholders.
Experience with code migration.
Experience with legacy systems (COBOL, JCL, DB2) or financial services (preferred); Master's in Computer Science (preferred).

Save