Senior Private Cloud AI Engineer - Staff Engineer

Overview

Staff-level engineer on HPE's Private Cloud AI platform, designing, developing and enhancing platform components and supporting AI workload enablement across infrastructure and customer deployments.

What you'll do

• 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.
• 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.
• 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.
• 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.
• 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'll need

• 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.
• 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.

Nice to have

• 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.

Details

• Hybrid role: works on average 2 days per week from an HPE office.
• Location: Bengaluru, Karnātaka, India.
• Job level: TCP_04.