AI Architect

. Design, govern, and lead implementation of enterprise-grade AI solutions .

Posted 11/9/2026full-timeKatowice • PolandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing enterprise-grade AI solutions, leveraging Generative AI, Machine Learning, and cloud technologies. Proficient in architecting scalable AI platforms and applying trusted AI practices for compliance and security.

Highest-signal resume keywords

AI Solution ArchitectureGenerative AI FrameworksMachine Learning ProficiencyCloud Technologies (Azure, AWS)Data Engineering Principles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningGenerative AILarge Language Models (LLMs)Data ModelingData GovernanceModel Lifecycle ManagementCI/CD PracticesPythonTensorFlow

Soft Skills

CollaborationLeadershipCommunication

Tools & Technologies

DockerKubernetesAzure AI StudioMLflowGit

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Engineering or Mathematics

Industry Keywords

AI GovernanceData QualityEnterprise StandardsAI TransformationMonitoring Frameworks

Tech Stack

Tools & technologies

AWSAzureCloudDockerKubernetesPythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, govern, and lead implementation of enterprise-grade AI solutions
Help clients unlock value from data and AI technologies
Work with business stakeholders, data scientists, engineers, and technology teams to define AI strategies
Architect scalable AI platforms and deliver solutions using Generative AI, LLMs, Machine Learning, NLP, MLOps, and cloud technologies
Translate complex business challenges into robust AI architectures
Define AI roadmaps, architecture standards, and governance frameworks
Apply trusted AI practices for fairness, transparency, accountability, security, and compliance
Drive MLOps, LLMOps, and DevOps practices, including CI/CD, monitoring, and model lifecycle management
Build and manage AI solutions using Docker, Kubernetes, Git, Azure AI Studio, MLflow, and CI/CD platforms
Design monitoring, observability, logging, and evaluation frameworks
Collaborate with software engineering, cloud, security, and operations teams on deployment and integration
Lead technical teams, architecture reviews, and client-facing AI transformation initiatives

Requirements

What you’ll need

Minimum 5 years of experience in AI, Machine Learning, Data Science, or Solution Architecture
Proven experience designing and implementing enterprise AI solutions and AI platforms
Strong understanding of machine learning, deep learning, Generative AI, and Large Language Models (LLMs)
Experience architecting end-to-end AI solutions from data ingestion and model development to deployment and monitoring
Knowledge and hands-on experience with Generative AI frameworks and applications
Proficiency in Python and familiarity with TensorFlow, PyTorch, LangChain, Hugging Face, and related ecosystems
Understanding of retrieval-augmented generation (RAG), agentic AI systems, vector databases, and modern AI orchestration frameworks
Experience with Azure or AWS, including cloud-native AI services
Strong knowledge of data architecture and data engineering principles, including data modeling, governance, integration, and data quality
Experience designing scalable and secure AI architectures following enterprise standards and best practices
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field

Benefits

Comp & perks

Continuous learning and skills development
Tools and flexibility to make a meaningful impact
Coaching and leadership development
Diverse and inclusive culture
Collaboration with global EY teams
Career opportunities across EY service lines, geographies and sectors