Lead Software Engineer- Performance Engineering + Python

Overview

• Own the end-to-end performance, scalability, and resilience strategy for the Tachyon/MLOps platform.
• Serve as the technical lead and single point of accountability for performance engineering outcomes.
• Define, design, and execute comprehensive performance testing across UI, API, microservices, and event-driven systems.
• Build scalable performance test frameworks and automation utilities using Python or Java.
• Identify performance bottlenecks across application layers (UI, API, database, infrastructure) and perform deep-dive root cause analysis.
• Analyze performance test results, create test plans, and document findings through PIAs and engineering artifacts.
• Lead complex technical initiatives and collaborate with cross-functional teams including development, QA, DevOps, and platform engineering.
• Optimize and tune application configurations for cloud environments (e.g., OCP, autoscaling, load balancing).
• Utilize APM tools (AppDynamics, OTEL) and analyze performance dumps (thread, heap, JFR) to diagnose issues.
• Create dashboards in Grafana and Splunk for observability, monitoring, and resource analysis.
• Implement performance engineering best practices across teams and mentor performance engineers.
• Develop custom scripts or automation workflows to support performance testing and environment validation.
• Assess risks early in the performance testing lifecycle and recommend mitigation strategies.
• Contribute to continuous improvement initiatives, process enhancements, and operational efficiency.
  
  

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  
  

• Strong proficiency in performance engineering across UI, API, microservices, and event-driven architectures.
• Hands-on expertise with performance testing tools such as LoadRunner Enterprise (LRE), JMeter, BlazeMeter, and DevTest for service virtualization.
• Advanced programming capabilities in Python and Java for building automation utilities, custom scripts, and performance tooling.
• Deep understanding of AI/ML, GenAI, and Agentic AI concepts as applied to performance engineering and platform scalability.
• Strong skills in performance bottleneck analysis across application, database, infrastructure, and cloud layers.
• Proficiency with APM tools (AppDynamics, OTEL) and experience analyzing thread dumps, heap dumps, and JFR profiles.
• Ability to design and tune performance for cloud-native microservices running on platforms such as OpenShift (OCP), including autoscaling and load balancer optimization.
• Skilled in creating observability dashboards and analyzing logs using Grafana and Splunk.
• Strong understanding of microservices architecture, event-driven systems, and distributed environments.
• Ability to write shell scripts for monitoring and resource capture on Unix environments.
• Demonstrated ability to assess risks early in the performance lifecycle and recommend mitigation strategies.
• Effective communicator with strong collaboration skills, able to work with development, DevOps, QA, and platform teams.
• Proven capability to lead performance engineering initiatives and mentor fellow engineers.
  
  

19 Feb 2026

• Job posting may come down early due to volume of applicants.
  
  

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

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R-517267