Hewlett Packard Enterprise
Hewlett Packard Enterprise
Hewlett Packard Enterprise develops enterprise technology for organizations running hybrid cloud and AI-driven operations. Its portfolio spans HPE ProLiant servers and HPE Cray high-performance computing, HPE Alletra storage, HPE Aruba networking, AI platforms and turnkey AI factories, and GreenLake as-a-service solutions. HPE also provides security capabilities such as Zero Trust and SASE, alongside professional, advisory, and support services that help large organizations modernize infrastructure, manage data-center environments, and deploy AI at scale.

Principal Cloud and AI Innovation Developer

Lead cloud-native and generative AI innovation at Hewlett Packard Enterprise. Shape incubation solutions, guide engineering teams, and build scalable services for cloud, datacenter, and edge environments.

Description

  • Contribute senior technical expertise to complex AI and cloud-native incubation work.
  • Design and deliver key components of proposed solutions.
  • Guide cross-disciplinary teams of up to six engineers from concept through development.
  • Assess and integrate emerging software technologies and generative AI frameworks.
  • Build and validate microservices and cloud-native systems for public cloud, datacenter, and edge deployments.
  • Help shape architecture for scalability, performance, security, and reliability.
  • Work with internal customers, technical leads, and business stakeholders.
  • Run research investigations, proofs of concept, and experiments.
  • Develop quality software using AI-assisted coding alongside sound testing, validation, CI/CD, and observability practices.
  • Coach colleagues in advanced software engineering and AI.
  • Manage several concurrent projects and shift focus as needed.

Requirements

  • Bachelor’s or master’s degree in computer science, information systems, AI/ML, or a related technical discipline.
  • Typically 10–15 years of software development experience.
  • At least 3–5 years working on cloud-native and AI/ML systems.
  • Strong Python programming skills.
  • Experience with machine learning libraries such as PyTorch, TensorFlow, and Transformers.
  • In-depth knowledge of distributed systems, microservices, and event-driven architectures.
  • Practical experience with Kubernetes, Docker, REST APIs, and cloud-native application development.
  • Experience building generative AI solutions with LLMs, RAG, LangGraph, or comparable frameworks.
  • Working knowledge of vector databases, graph databases, NoSQL, and relational database systems.
  • Experience deploying cloud solutions on AWS, Azure, or Google Cloud Platform.
  • Strong understanding of AI governance, security alignment, and responsible AI principles.
  • Proficiency in Agile methods, including Scrum or Kanban.
  • Experience contributing to large-scale cloud service development.
  • Experience with multi-agent systems and agent orchestration frameworks.
  • Knowledge of developing Model Context Protocol (MCP) servers.
  • Understanding of Google ADK and A2A protocol implementations.
  • Knowledge of designing, building, and querying knowledge graphs.
  • Familiarity with ML Ops tools such as MLflow, Weights & Biases, and LangSmith.
  • Experience with observability platforms such as Prometheus, Grafana, or OpenTelemetry.

Benefits

  • Benefits designed to support physical, financial, and emotional wellbeing.
  • Programs for personal and professional growth.
  • Flexible work arrangements to help balance work and personal needs.
  • An inclusive workplace culture.
  • Variable incentives may be available.

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