Level

Hewlett Packard Enterprise

Senior Private Cloud AI Engineer - Staff Engineer

Hewlett Packard Enterprise is hiring a Senior Private Cloud AI Engineer - Staff Engineer in Bengaluru, India. Level rates it ; you can apply on Hewlett Packard Enterprise.

Level's read on this job

  • On Level's scale, this AI engineer role is Little AI ●○○○: aI is not part of the work.
  • The posting mentions RAG and MLOps among its tools and skills.
  • Level classes it as a lead role.
  • Hewlett Packard Enterprise has 1,600+ other open roles on Level.
  • Posted in the last few days.

AI in this role

ragml-ops
Senior Private Cloud AI Engineer - Staff Engineer

  

This role has been designed as 'Hybrid' with a requirement 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:

   

HPE Hybrid Cloud, we lead the innovation agenda and technology roadmap for all of HPE. This includes managing the design, development, and product portfolio of our next-generation cloud platform, Green Lake. Working with customers, we help them reimagine their information technology needs to deliver a simple, consumable solution that helps them drive their business results. Join us redefine what’s next for you. 


What you’ll do:

Key Responsibilities

Platform Engineering & Development

  • Design, develop, and enhance components of the HPE Private Cloud AI platform.
  • Build automation, tooling, APIs, and workflows that improve deployment, operations, monitoring, and lifecycle management.
  • Contribute to Kubernetes-based platform services and cloud-native capabilities.
  • Participate in architecture reviews, design discussions, and technical roadmap planning.

AI Platform Enablement

  • Support integration of AI technologies into the platform.
  • Enable workloads leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), model serving frameworks, and MLOps tools.
  • Evaluate and integrate emerging AI technologies, frameworks, and development tools.
  • Assist in testing, validating, and operationalizing AI workloads on enterprise infrastructure.

Infrastructure & Systems Integration

  • Collaborate across compute, networking, storage, virtualization, and operating system domains to deliver end-to-end solutions.
  • Assist with platform integration, deployment validation, performance tuning, and troubleshooting.
  • Identify and resolve system-level issues spanning hardware, infrastructure, platform software, and applications.
  • Contribute to infrastructure automation and operational efficiency initiatives.

Customer & Solution Engineering

  • Partner with product management, support, field engineering, and customer teams to address real-world deployment challenges.
  • Investigate customer-reported issues, identify root causes, and drive resolution across engineering teams.
  • Support proof-of-concepts, reference architectures, and customer adoption initiatives.
  • Translate customer feedback into actionable product and engineering improvements.

Continuous Improvement & Innovation

  • Identify opportunities to simplify deployment, improve reliability, and enhance customer experience.
  • Participate in performance, scalability, reliability, and operational readiness activities.
  • Contribute to documentation, best practices, and knowledge sharing across the organization.
  • Stay current on cloud, infrastructure, AI, and automation technologies relevant to HPE's AI strategy.

 What you need to bring:

Education and Experience Required:

Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, Electrical Engineering, or a related technical field.

Minimum of 10 years of applicable work experience.


Required Qualifications
  • Experience in software engineering, systems engineering, platform engineering, infrastructure engineering, or a related technical discipline.
  • Proficiency in one or more programming languages such as Python, Go, Java, C++, or similar.
  • Experience developing automation, scripts, APIs, or operational tooling.
  • Experience with Kubernetes, containerized environments, and cloud-native architectures.
  • Working knowledge of Linux operating systems and enterprise infrastructure technologies.
  • Strong troubleshooting and debugging skills across distributed systems.
  • Ability to work effectively across multiple technical domains and engineering organizations.
  • Strong communication and collaboration skills.

 

Preferred Qualifications

  • Experience with infrastructure automation tools such as Ansible, Terraform, Helm, or related technologies.
  • Familiarity with public or private cloud platforms and virtualization technologies.
  • Experience supporting large-scale enterprise platforms or distributed systems.
  • Exposure to AI/ML development frameworks and workflows.
  • Familiarity with Large Language Models (LLMs), RAG architectures, vector databases, model deployment, or MLOps technologies.
  • Experience troubleshooting production systems and customer-facing environments.
  • Knowledge of GPU-accelerated computing, high-performance networking, or AI infrastructure.

Accessibility


HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.


Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

Job:

Engineering

Job Level:

TCP_04

    

    

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

   

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

   

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

How we rate this

Senior Private Cloud AI Engineer - Staff Engineer at Hewlett Packard Enterprise rates 4 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML Ops

Also common in AI engineer jobs at this level

Pay

Typical AI engineer job
$186k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?

Adapt your resume

  • List these exact terms on your resume: RAG and ML Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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