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. Open up opportunities with HPE.

Customer Onboarding

• 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.

Customer Engagement

• 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.

Use Case Adoption

• 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.

Collaboration and Coordination

• 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.

Customer Success

• 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.

Our technical stack

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

Your past experience

• 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)

Minimum requirements

• Project Management:
  Demonstrated expertise in managing multiple complex projects simultaneously, with a proven track record of prioritizing tasks and meeting deadlines efficiently and effectively.
• Customer Service:
  Strong customer service orientation, with a focus on delivering exceptional support.
• Technical Troubleshooting and Problem Resolution:
  Strong analytical and problem-solving skills to quickly identify issues, and work with support team to resolve.
• Communication:
  Excellent verbal and written communication skills, with the ability to explain complex technical concepts clearly.
• Collaboration:
  
  Strong teamwork skills and the ability to work collaboratively with cross-functional teams.
• Empathy:
  Ability to understand and empathize with customer challenges and provide supportive solutions.
• Proactive Approach:
  Initiative to anticipate customer needs and address potential issues before they arise.
• Attention to Detail:
  Keen attention to detail to ensure accurate and thorough support and documentation.

Additional Skills

Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, Dev Ops, Distributed Computing, Microservices…