Lead Escalation Engineer

Hewlett Packard Enterprise is seeking a Lead Escalation Engineer in our San Jose, California office. As a Lead Escalation Engineer, you will lead the resolution of complex and high-profile customer escalations involving enterprise wireless, cloud-managed and AI-native networking solutions.

Responsibilities:

• Own and drive complex, high-severity customer escalations from initial triage through recovery, root-cause identification and permanent resolution.
• Lead critical technical investigations and war rooms, working closely with TAC, Support, Development and QA across wireless, wired, cloud and network services.
• Analyze telemetry, logs, packet captures, crashes and customer topology; reproduce complex issues in the lab and systematically isolate failures across software, hardware, cloud and client environments.
• Drive customer-found defects through engineering, develop clear RCA and corrective-action plans, and advocate for product quality, reliability, serviceability and observability.
• Build troubleshooting tools, automation, playbooks and AI-assisted diagnostic workflows that improve triage, knowledge discovery, root-cause analysis and future resolution efficiency.
• Identify recurring escalation patterns, translate field learnings into proactive quality and automated remediation improvements, and mentor engineering teams as Escalation Engineering evolves toward more proactive and AI-assisted operations.

Basic Job Requirements:

• 8+ years of professional experience in Escalation Engineering, Technical Support, Systems Engineering, SQA/Quality Engineering or a related networking role.
• Strong troubleshooting and debugging experience with enterprise WLAN and networking systems.
• Demonstrated ability to systematically troubleshoot complex problems involving multiple technologies and components.
• Strong understanding of Wi-Fi system-level testing, characterization and troubleshooting.
• Ability to operate effectively during high-pressure customer situations and critical production incidents.
• Ability to collaborate across Support, Engineering, QA and Product Management organizations.
• Demonstrated ability to independently drive complex technical investigations with limited supervision.
• Strong customer focus combined with disciplined and data-driven engineering practices.

Qualifications:

• Bachelor of Science in Computer Science, Computer Engineering, Electrical Engineering or a related field with 8+ years of relevant experience, or MS with 6+ years; networking certifications such as CCNA, CCNP or CWNP are highly desirable.
• Strong expertise in Layer 2/Layer 3 networking, TCP/IP, IPv4/IPv6, OSPF, enterprise authentication, and deep knowledge of Wi-Fi 6/6E with familiarity with Wi-Fi 7.
• Hands-on troubleshooting experience with Wireshark/tcpdump, Linux, virtualization, cloud environments such as AWS/Azure, and cloud-managed, SaaS or distributed systems.
• Experience with Python, REST APIs, JSON, scripting, automation, telemetry and observability for troubleshooting, data collection and operational workflows.
• Working knowledge of Generative AI and AI-assisted engineering tools, including LLM-based troubleshooting, log analysis, knowledge retrieval, case summarization, RAG/agentic workflows, and tools such as ChatGPT, Claude, Gemini or GitHub Copilot.

What Success Looks Like:

• Critical customers recover quickly and receive strong technical leadership throughout major incidents.
• Complex problems are converted into clearly understood root causes and permanent engineering solutions.
• Recurring issues result in better product design, diagnostics, test coverage and serviceability.
• Troubleshooting knowledge becomes reusable automation, playbooks and AI-assisted workflows.
• Product telemetry and observability continue to improve based on real-world customer experience.
• Support teams become more effective through mentoring, automation and better diagnostic capabilities.
• Lessons learned from today's hardest customer problems become part of the intelligence that helps tomorrow's network detect, diagnose and ultimately resolve problems autonomously.