Principal Engineer - AI Architect

About the role

Hewlett Packard Enterprise is seeking an AI Architect, a senior technical leader who designs and oversees end-to-end AI systems aligned with business objectives. The role bridges business strategy and technical execution, ensuring scalability, security and compliance across AI solutions. It is a hybrid position with an expectation of working about 2 days per week from an HPE office.

Key responsibilities

• Design end-to-end AI systems, from data ingestion through model deployment to user interface.
• Work with AI/ML engineers, data engineers and MLOps teams to ensure production readiness.
• Define the AI roadmap aligned with organizational goals, identify high-impact use cases and assess ROI, and engage stakeholders early on feasibility and governance.
• Design AI system architecture (data pipelines, model lifecycle, orchestration), integrate AI with enterprise apps, and ensure scalability, fault tolerance and cost efficiency.
• Select ML/DL models and frameworks (TensorFlow, PyTorch), define versioning, fine-tuning and deployment strategies, and implement CI/CD for ML pipelines and monitoring.
• Enforce data privacy, ethical AI practices and audit trails, set guardrails for LLMs and prompt safety, and work with security teams on risk mitigation.
• Mentor engineers and data scientists, translate business requirements into technical tasks, and drive collaboration across product, data and operations teams.

Required profile

• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence or a closely related quantitative discipline.
• Typically 10+ years of experience.
• Good networking knowledge.
• Strong communication skills to explain complex AI concepts to non-technical stakeholders and lead junior engineers.

Required skills

• Python, Java, Node.js, API design and microservices.
• AWS, Azure, GCP and container orchestration (desirable).
• AI/ML algorithms, LLMs, RAG and agent-based systems; TensorFlow, PyTorch, Hugging Face.
• MLOps, Docker/Kubernetes, and data architecture (ETL, feature stores, vector databases).

What we offer

• Benefits supporting physical, financial and emotional wellbeing.
• Programs for personal and professional development.
• An inclusive workplace with flexibility to manage work and personal needs.