Senior Technical Marketing Engineer – Service Provider

Senior Technical Marketing Engineer – Service Provider

  

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are:

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.

Job Description:

   

Senior Technical Marketing Engineer – Service Provider

About the Position

HPE Juniper Networking is seeking a senior, passionate, and highly motivated Senior Technical Marketing Engineer to drive and own technical marketing activities with an emphasis on Service Provider—5G xHaul, Cloud Metro, Broadband Edge, and Telco markets, and to be a primary contributor to HPE Juniper Service Provider and AI-era architectures.

This individual will be part of HPE Juniper’s TME and PLM organization and a strategic partner to go-to-market and R&D engineering teams to define, advocate for, and drive the evolution of the product portfolio, including new solutions for AI workloads and Service Provider AI architectures (e.g., AI/ML training and inference fabrics, AI-ready transport, and edge AI services) and cloud-delivered services.

This role is a key senior individual contributor position that requires leadership across cross-functional teams—engineering, QA/test, product management, marketing, sales, and systems engineering—to execute against HPE Juniper’s growth strategy in the AI and Cloud Metro era.

Responsibilities

The ideal candidate is execution-oriented, has a builder mentality, strong technical acumen, and is comfortable spanning deep technology and customer-facing business conversations. Essential responsibilities include:

• Act as technical advisor and go-to subject matter expert for targeted platforms and solutions; help product teams drive Service Provider, AI-ready transport, and xHaul platform strategy, product definition, and program execution.
• Develop a coherent solution story focused on:
  • 5G (and emerging 6G-ready) xHaul and Open RAN/Cloud RAN transport
  • Cloud Metro and Broadband Edge architectures
  • Cable DAA, FWA, and converged IP service edge
  • Service Provider AI architectures and AI-centric use cases, including AI data center interconnect, AI/ML clusters, and distributed inference/edge AI.
• Communicate value propositions, architectures, and implementation details to customers and internal sales organizations by:
  • Developing technical collateral (white papers, solution briefs, reference designs, validated designs)
  • Delivering live webinars, conference sessions, and technical demos
  • Contributing content to blogs, videos, and Git/GitHub-hosted assets (lab guides, code samples, configs).
• Design and implement compelling Proof of Concept (PoC) lab setups and demos for SP and Cloud Metro / AI solutions, including:
  • Segment Routing (SR-MPLS and/or SRv6) and SR-TE/SR Policies
  • Advanced EVPN services (e.g., EVPN-VPWS/ELAN/ETREE, L3VPN)
  • Traffic engineering and fast reroute (e.g., TI-LFA)
  • Integration with automation frameworks and CI/CD.
    Document results clearly and maintain demos so they are reproducible by sales and SE teams.
• Drive network automation and telemetry blueprints, including:
  • Design of workflows using NETCONF/gNMI, YANG models, REST/JSON APIs, Ansible, Terraform, Python, and/or controller platforms (e.g., Routing Director or similar).
  • Definition and validation of streaming telemetry and observability architectures (gNMI, model-driven telemetry, Kafka/data-lake ingestion, dashboards, closed-loop automation).
• Translate AI workload requirements into transport and metro network architectures, including capacity planning, latency/jitter constraints, traffic engineering (segment routing/SRv6 policies), QoS, and multi-tenant isolation.
• Produce competitive analysis collateral that highlights HPE Junipers’ strengths and areas for improvement (features, scale, performance, TCO, operational model) and keep it current with market evolution.
• Evangelize HPE Juniper’s vision f