Private Cloud AI Customer Engineer

Private Cloud AI Customer Engineer

This role has been designated as Remote/Teleworker, which means you will primarily work from home.

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.

Global Sales at HPE is about building the future. We are redefining what’s next and combining our legacy of innovation with a bold new goal to accelerate everything we do. Our sales organization is comprised of 10,000+ professionals in sales, presales, service, and support functions. Together with our partners, we deliver global, commercial, public sector & small/medium business customers throughout 11 geographies.

We’re transforming businesses. Join us to redefine what’s next for you.

As a Private Cloud AI PCAI Customer Engineer, you will be a crucial member of our technical and customer-facing team, supporting the HPE Private Cloud AI PCAI product. Your primary responsibility will be to assist customers with hands‑on support during the first three months post-purchase. You will guide customers through the initial adoption of their first use case, providing informal product training, and conducting regular cadence calls with customers and internal stakeholders.

You will coordinate with multiple teams to ensure the customer receives early value from the product, ensuring success and contract renewals.

• Assist customers in the initial adoption of the HPE PCAI Private Cloud AI product.
• Project manage the customer and use case.
• Provide hands‑on support and guidance during the first three months post-purchase.
• Conduct informal product training sessions to help customers understand and utilize the product effectively.

• Schedule and conduct regular cadence calls with customers to track progress, address concerns, and provide updates.
• Serve as the primary point of contact for customers during the onboarding phase, ensuring a smooth and positive experience.

• Guide customers through the initial adoption of their first use case, providing technical expertise and best practices.
• Work closely with customers to understand their specific requirements and tailor support accordingly.

• Collaborate with internal teams, including Sales, Product Management, and Technical Support, to ensure customer success.
• Coordinate with multiple stakeholders to address customer needs, resolve issues, and ensure timely delivery of solutions.

• Monitor customer progress and provide proactive support to ensure early value realization from the product.
• Identify potential challenges and work with customers to mitigate risks and ensure a successful onboarding experience.
• Track customer satisfaction and feedback, and work with internal teams to continuously improve the onboarding process.

• Kubernetes
• Python
• S3
• Presto
• Airflow
• Superset
• Spark
• Livy
• Kubeflow
• MLflow
• Ray
• MLIS
• Feast
• NVIDIA AI Enterprise

• Python (hands‑on with data science libraries preferred)
• Linux
• Kubernetes (GPU Scheduling)
• Containerization (including repositories, creating container images, etc)
• Helm
• AuthN/AuthZ (including SSO)
• Lang Chain, Llama Index, vLLM
• RAG Pipelines
• Storage (object, file)
• Big Data (structured vs unstructured) and storage solutions (data warehouses, lakes, distributed file systems)
• Relational Database Management System (RDBMS)
• SQL and No
  
  SQL
• NLP (and its limitations)
• LLMOps
• Vector DBs
• Enterprise AI solutions and techniques (Virtual assistants, Q&A chatbots, summarization, RAG, etc)

• Project Management:
  Dem…