Senior Private Cloud AI Engineer - Staff Engineer

Location: Bengaluru, Karnātaka, India

Senior Private Cloud AI Engineer - Staff EngineerThis role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.

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.

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.

Job:

Engineering

Job Level:

TCP_04

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.

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