Principal Cloud Developer - AI/ML

The Cloud Developer builds from the ground up to meet the needs of mission-critical applications, and is always looking for innovative approaches to deliver end-to-end technical solutions to solve customer problems.

Brings technical thinking to break down complex data and to engineer new ideas and methods for solving, prototyping, designing, and implementing cloud-based solutions.

Collaborates with project managers and development partners to ensure effective and efficient delivery, deployment, operation, monitoring, and support of Cloud engagements.

The Cloud Developer provides business value expertise to drive the development of innovative service offerings that enrich HPE's Cloud Services portfolio across multiple systems, platforms, and applications.

Contributions have visible technical impact on a product or major subcomponent.  Applies in-depth professional knowledge and innovative ideas to solve complex problems. Visible contributions improve time-to-market, achieve cost reductions, or satisfy current and future unmet customer needs. Recognized internal authority on key technology area applying innovative principles and ideas. Provides technical leadership for significant project/program work. Leads or participates in cross-functional initiatives and contributes to mentorship and knowledge sharing across the organization.

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  Own end-to-end architecture and technical roadmap for data-intensive and AI-enabled enterprise applications.

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  Design scalable, secure, resilient cloud-native solutions for application, data, and AI workloads.

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  Lead architecture reviews, technical governance, and technology selection.

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  Drive engineering best practices including TDD, code reviews, CI/CD, automation, and MLOps/LLMOps practices.

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  Architect data platforms, APIs, microservices, distributed systems, and AI service integration patterns.

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  Lead the design and operationalization of AI/ML solutions, including model deployment, monitoring, drift detection, and retraining strategies.

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  Evaluate and implement Generative AI use cases such as LLM-powered assistants, RAG architectures, prompt orchestration, and agent-based workflows where relevant.

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  Establish observability, monitoring, reliability, incident response, and governance practices for both software and AI systems.

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  Mentor engineers and influence technical direction across teams.

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  Partner with Product, Security, Infrastructure, Data Science, and Business stakeholders.

Lead the architecture, engineering, and operational excellence of cloud-native, data-intensive enterprise applications. Own technical strategy, platform scalability, reliability, cloud operations, and engineering excellence while providing hands-on technical leadership.

• 12+ years of software engineering experience.
• 5+ years in architecture or technical leadership roles.
• Expertise in programming languages like Java, Python, or Go, Framework like ReactJS, Angular and NodeJS.
• Strong OOAD, design patterns, microservices, and distributed systems experience.
• Strong API design experience using REST, JSON/XML, Swagger, and Postman.
• Experience with PostgreSQL, SQL Server, Oracle, and exposure to NoSQL databases.
• Experience with Linux/Unix, HTTP, caching, scalability, and performance optimization.
• Agile/Scrum, TDD, unit testing, and troubleshooting expertise.
• Strong understanding of AI/ML fundamentals, model lifecycle, feature engineering, and production deployment patterns.
• Hands-on experience with AI/ML frameworks and platforms such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
• Experience building or integrating Generative AI solutions using LLMs, prompt engineering, embeddings, vector databases, and RAG patterns.
• Knowledge of MLOps/LLMOps practices including model versioning, evaluation, monitoring, experimentation, and governance.
• Ability to assess AI solution trade-offs across accuracy, latency, scalability, security, explainability, and cost.

• Effectively communicate product architectures, design proposals, and negotiate options at business unit and executive levels.

• AWS and/or Azure/GCP cloud platforms.
• Infrastructure as Code (Terraform, CloudFormation).
• Monitoring, Observability, SRE, and Platform Engineering practices.
• Experience with AI platform services such as Amazon Bedrock, SageMaker, Azure OpenAI, Vertex AI, or equivalent.
• Familiarity with vector databases, model serving and inference optimization.
• Knowledge of responsible AI, model governance, privacy, and security considerations for enterprise AI adoption.

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.

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.

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.

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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