Lead Software Engineer, Python, GenAI

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Plano, TX
Employment: Full-time
Posted: 19 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $201k

$140k $249k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $177,250–$225,000.

Based on 240 similar postings.

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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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Python, GenAI

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JOB TITLE: Lead Software Engineer - Python - GenAI As a Lead Software Engineer within Corporate Technology, you will join an agile team to build and deliver trusted, scalable technology products. You will architect and implement resilient, low-latency services while leading and mentoring a development team in a high-pressure environment. Your daily work involves productionalizing ML models for fraud detection and risk assessment, building agentic AI services with tool integration, and designing reusable ML platform components like feature-store patterns. You will utilize Python, Java, and Kubernetes to manage microservices, REST APIs, and messaging platforms like Kafka or MQ. Key responsibilities include managing ML pipelines, ensuring security and auditability, and driving the adoption of AI-assisted engineering practices. You must navigate complex distributed systems using Linux, NoSQL databases like Cassandra, and observability tools like ELK or Splunk.

Skills

Python Java Kubernetes AWS MLOps Kafka Cassandra REST APIs Microservices CI/CD Linux ELK Splunk Agentic AI LLM NoSQL Distributed Systems SDLC Monitoring Telemetry

What you'll do

Architect and implement resilient, highly scalable, and low-latency services for production environments.
Design and deploy services that integrate with enterprise systems while meeting security and auditability requirements.
Lead and mentor the development team to manage multiple deliverables across various business groups.
Build and mature ML pipelines for fraud detection and risk assessment.
Productionalize data science models by establishing validation readiness and quality controls.
Build agentic AI services to automate engineering and model-ops workflows with audit-ready traceability.
Define and implement guardrails for agentic AI regarding quality, safety, latency, and cost.
Drive team adoption of AI-assisted engineering practices to improve code quality and delivery speed.

What we're looking for

Formal training or certification in software engineering concepts and 5+ years of applied experience.
Hands-on experience in system design, application development, testing, and operational stability for large-scale distributed systems.
Deep expertise in Python and Java, specifically for AI/ML engineering, automation, and microservices architecture.
Experience developing in Linux environments and using Kubernetes for building, deploying, and operating production services.
Proficiency with messaging platforms like Kafka or MQ, and backend patterns including load balancing, autoscaling, and NoSQL databases.
Strong knowledge of SDLC, CI/CD, agile methodologies, and observability tools like ELK or Splunk.
Experience building and operating LLM-driven agentic AI services with tool integration, monitoring, and governance.
AWS Certification(s) and/or working knowledge (preferred); AI Certification(s) and/or working knowledge (preferred).

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