Cloud Architect specializing in Ansible and automation solutions at Red Hat. Leading consulting teams and ensuring successful customer deployments while fostering a world - class customer experience.
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
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