Principal Cloud Developer - AI/ML

Job description

Principal Cloud Developer - AI/MLThis role has been designed as Hybrid with a requirement that you will work on average 2 days per week from an HPE office. ***Job Family Definition:*** 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 HPEs Cloud Services portfolio across multiple systems, platforms, and applications. ***Management Level Definition:*** 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. **What you ll do:** **Position Summary** 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. **Key Responsibilities** - Own end-to-end architecture and technical roadmap for data-intensive and AI-enabled enterprise applications. - Design scalable, secure, resilient cloud-native solutions for application, data, and AI workloads. - Lead architecture reviews, technical governance, and technology selection. - Drive engineering best practices including TDD, code reviews, CI/CD, automation, and MLOps/LLMOps practices. - Architect data platforms, APIs, microservices, distributed systems, and AI service integration patterns. - Lead the design and operationalization of AI/ML solutions, including model deployment, monitoring, drift detection, and retraining strategies. - Evaluate and implement Generative AI use cases such as LLM-powered assistants, RAG architectures, prompt orchestration, and agent-based workflows where relevant. - Establish observability, monitoring, reliability, incident response, and governance practices for both software and AI systems. - Mentor engineers and influence technical direction across teams. - Partner with Product, Security, Infrastructure, Data Science, and Business stakeholders. **What you need to bring:** **Required Qualifications** - 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. **Preferred Qualifications** - 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. **Job:** Engineering **Job Level:** TCP\\_05 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 . **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 affiliat