Senior Software Engineering Manager

Hewlett Packard Enterprise•Sunnyvale, CA

3d•$135,500 - $275,000•Hybrid

About The Position

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Senior Software Engineering Manager – AI Data Center Networking Location: Sunnyvale, CA Lead a geographically distributed team of solutions and test engineers responsible for architecting, validating, and publishing Juniper Validated Designs (JVDs) across AI/ML cluster, data center, DCI, and campus portfolios. The manager owns team delivery, people development, lab and testbed investment, and cross-functional alignment for NPI programs, while remaining technically credible enough to guide architecture decisions and customer escalations.

Requirements

12+ years in network engineering, solutions validation, or systems test, with 3+ years leading teams (formally or as technical lead of distributed engineers).
Demonstrated record of mentoring engineers, driving cross-functional programs, and resolving customer escalations.
Proven ability to own delivery commitments, prioritize across competing programs, and make release-quality decisions.
Strong written and executive communication skills, including presenting to customers and senior leadership.
Deep expertise in data center fabrics: EVPN-VXLAN, IP Clos, CRB/ERB, underlay/overlay design.
Strong command of L2/L3 and multicast protocols: BGP, OSPF, IS-IS, BFD, PIM, IGMP.
Hands-on AI/ML cluster networking experience: RDMA/RoCEv2, congestion control (DCQCN, ECN, PFC), and load balancing.
Experience building test automation frameworks (Python, Robot Framework) and large-scale, customer-representative testbeds.
Bachelor's degree in engineering or a related field.

Nice To Haves

Prior formal people-management experience, including hiring, performance reviews, and compensation planning.
Budget or capital planning experience for labs and test infrastructure.
Experience with GPU platforms (NVIDIA A100/H100, AMD MI300X) and NICs (ConnectX, Pollara), including JCT-based performance benchmarking.
DCI expertise: EVPN-MPLS, L3VPN, Type-2/Type-5 stitching.
Campus and branch solution experience: EVPN multihoming, distributed gateway, filter-based forwarding.
Familiarity with traffic generators and analysis tools (Spirent, IXIA, Wireshark).
JNCIP-DC or equivalent certification.
Published validated designs, white papers, or conference presentations.

Responsibilities

Manage, hire, and develop a global team of solutions engineers, including goal setting, performance reviews, career planning, and compensation input.
Build team autonomy through coaching and mentoring, and develop a succession pipeline of senior and principal engineers.
Foster a culture of quality ownership, collaboration, and continuous learning across sites and time zones.
Own the solution validation roadmap and quarterly commitments for NPI programs, from multi-feature testing through scale validation and JVD publication.
Plan capacity, prioritize work across competing programs, and manage schedule risk and dependencies.
Define and report team metrics: release quality, defect escape rate, automation coverage, JVD delivery, and escalation turnaround.
Act as a release quality gate, with authority to hold releases that do not meet customer-readiness criteria.
Set technical direction for AI/ML data center validation: scale-out and scale-up GPU fabrics, RoCEv2, load balancing (DLB, GLB, RLB), congestion control (DCQCN, ECN, PFC), multi-tenancy, and JCT-based performance measurement.
Guide architecture for EVPN-VXLAN fabrics, DCI (EVPN-MPLS, Type-2/Type-5 stitching), and campus/branch solutions.
Drive the automation strategy (Python, Robot Framework) and sponsor reusable, topology-independent frameworks.
Plan and justify lab, GPU, NIC, and test equipment investments.
Manage testbed utilization and capital requests.
Partner with Product Management, TME, SE, JTAC, and development engineering on solution definition, POCs, and product strategy.
Serve as management escalation point for critical customer issues in AI cluster, data center, and campus deployments.
Sponsor white papers, JVDs, and customer-facing technical content.