Lead Infrastructure Engineer

About this role: Wells Fargo is seeking an experienced Lead Infrastructure Engineer to lead the design, development, and evolution of our enterprise observability and telemetry platforms . This role is critical to driving modern logging, monitoring, and AI‑driven insights using Splunk, Cribl, IT Service Intelligence (ITSI) , and agentic AI systems . You will play a hands‑on technical leadership role—owning architecture decisions, driving automation, mentoring engineers, and partnering with platform, SRE, and security teams to deliver scalable, resilient, and intelligent observability solutions across hybrid and cloud environments. In this role, you will: Own the architecture, reliability, and scalability of enterprise logging platforms. Lead design and implementation of high‑volume, resilient log ingestion pipelines across hybrid and cloud environments. Define and enforce logging standards, schemas, and governance aligned with enterprise observability strategy. Design and integrate AI/ML models for anomaly detection, log classification, predictive alerting, and signal enrichment. Build and operationalize agentic AI systems capable of: Autonomous log analysis and root‑cause hypothesis generation Context‑aware remediation recommendations Intelligent correlation across logs, metrics, and traces Partner with platform and SRE teams to embed AI‑driven insights into incident response workflows . Partner with security and compliance teams to support auditability, retention, and access controls .

5+ years of Technology Infrastructure Engineering and Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: 8+ years of experience in software engineering or platform engineering Deep expertise with Splunk Enterprise / Splunk Cloud , including search optimisation, index design, and platform operations. Proven hands‑on experience with Cribl (Stream / Edge) for telemetry pipeline optimisation. Strong experience with Splunk ITSI , service modelling, KPIs, and episode management Hands‑on experience with agentic AI frameworks or autonomous agents (LLM‑based or rule‑driven). Strong understanding of prompt engineering, tool‑using agents, feedback loops, and guardrails . Proficiency in one or more languages: Python, Java, Go, or Scala . Worked on a large Splunk infrastructure, including clustered environments, multi-site deployments, and cloud/SAAS deployment. Exposure to containerization and orchestration tools (Docker, Kubernetes). Familiarity with DevOps practices and CI/CD pipelines. Certifications in Splunk, Cribl, or cloud technologies (AWS, Azure). Experience applying AI/ML techniques to operational or telemetry data. Job Expectations: Develop complex dashboards, reports, and alerts tailored to business and operational needs. Develop migration strategies, including data ingestion, configuration, and app compatibility assessments. Design data pipelines to optimize Splunk ingestion, reduce licensing costs, and improve system performance. Proactively identify and resolve bottlenecks in ingestion, indexing, and search processes. Experience with cloud platforms , containerization, and Kubernetes/OpenShift. Familiarity with Open Telemetry , observability standards, and telemetry correlation. Posting End Date:   9 Sep 2026 *Job posting may come down early due to volume of applicants. We Value Equal Opportunity 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. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes