Lead Software Engineer, AI

JPMorgan Chase

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Plano, TX
Employment: Full-time
Posted: 33 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $194k

$158k most similar roles pay here $232k

This listing doesn't post a salary. Most similar roles pay $173,350–$215,325.

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 1174 open roles on FindRole.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Lead Software Engineer, AI

Role Posting Log in to save

Lead Software Engineer - AI, Python/Java joins the Firmwide AI/ML Deployment Platform team to build and deploy an AI solution unifying observability data across AWS, Azure, and GCP environments. The role involves designing pipelines to ingest telemetry data like metrics, logs, and traces to create automated troubleshooting recommendations and predictive self-healing systems. You will develop infrastructure for control plane integration, implement closed-loop automation playbooks, and operationalize LLM models for anomaly detection and forecasting. Key responsibilities include driving team adoption of AI-assisted engineering practices and building conversational interfaces for non-expert users. Required skills include Python, Java, and experience with NLP, time-series forecasting, and agentic AI concepts. You will utilize tools like Snowflake, OpenTelemetry, Prometheus, and Dynatrace while integrating with ticketing systems like ServiceNow or Jira Service Management to reduce mean time to resolution.

Skills

Python Java LLM Machine Learning AWS Azure GCP OpenTelemetry Prometheus Dynatrace Snowflake React NLP RAG API Jira Service Management ServiceNow

What you'll do

Design and build infrastructure solutions to integrate control planes and user accounts across multi-cloud environments.
Develop pipelines to ingest, aggregate, and correlate telemetry data including metrics, logs, and traces from AWS, Azure, and GCP.
Architect and implement closed-loop automation playbooks for self-healing infrastructure and automated remediation of common failure modes.
Build and operationalize LLM and machine learning models for anomaly detection and predictive system health monitoring.
Integrate AI engines with ticket data to cluster repetitive issues and reduce Mean Time to Resolution (MTTR).
Create conversational AI interfaces or self-service portals to allow non-expert teams to diagnose and fix infrastructure issues.
Drive team adoption of AI-assisted engineering practices to improve code quality, delivery speed, and automated testing.
Establish validation standards for secure coding and ensure the responsible use of AI in engineering workflows.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Proficiency in Python and Java, including experience integrating LLM/ML models and understanding agentic AI concepts.
Expertise in multi-cloud architectures across AWS, Azure, and GCP, including on-premise environments.
Experience with enterprise observability stacks such as OpenTelemetry, Prometheus, and Dynatrace.
Competency in managing large-scale streaming data infrastructure using cloud-native warehouses like Snowflake.
Advanced experience with configuration management tools, automated workflow engines, and building custom webhooks or APIs for ticketing systems.
Demonstrated experience leading the use of approved AI-assisted software development tools while ensuring security and quality standards.
Experience in API design, React framework proficiency, and applying generative AI to accelerate development (preferred).

Save