Hybrid AI Automation Architect

at Hewlett Packard Enterprise

• Job title: AI Automation Architect
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: $172,000 - $349,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Python, PyTorch, Scikit-Learn, Tensorflow
• Location requirements: Hybrid, Spring, United States

About the role

• AI-Automation Architect responsible for deploying AI and automation solutions at HPE. Collaborating with business leaders to improve processes and productivity through technology.

Responsibilities

• Assess business processes and identify opportunities where automation and AI can remove manual effort and improve productivity.
• Define technical architectures for automation and AI solutions, covering workflow orchestration, data needs, integrations, and model or rules-based components.
• Advise stakeholders on feasibility, solution options, and expected impact; convert business requirements into clear technical designs.
• Work hands-on with engineering teams to ensure solutions are built, tested, and deployed correctly, providing guidance during implementation.
• Evaluate emerging AI and automation technologies, run proofs-of-concept, and recommend adoption where they add value.
• Conduct design reviews to ensure consistency, quality, and adherence to architectural standards across projects.
• Mentor engineers and contribute to building reusable patterns, best practices, and long-term automation strategies.
• Prepare concise technical documentation and executive-level presentations that clearly explain solution design and business impact.

Requirements

• Bachelor’s or master’s degree in computer science, engineering, data science, AI, or related quantitative field.
• Typically 10–15 years of experience in automation architecture, AI/ML engineering, or enterprise solution design.
• Strong understanding of applied AI concepts, including supervised/unsupervised learning, NLP, conversational AI, embeddings, vector search, and rules-based automation.
• Hands-on experience integrating ML models and AI services into production systems; familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, and modern LLM/agent tooling.
• Proficiency in Python and/or other engineering languages, with ability to produce maintainable code and automation logic.
• Experience designing data pipelines, performing data preparation, and ensuring data quality for automation and AI workloads.
• Demonstrated commitment to continuous learning and staying current with AI, automation, agentic frameworks, and orchestration technologies.
• Experience mentoring engineers, guiding design reviews, and influencing architectural decisions across teams.
• Strong communication skills for engaging stakeholders, explaining complex concepts, and aligning technical recommendations to business outcomes.

Benefits

• Health & Wellbeing
• Personal & Professional Development
• Unconditional Inclusion