EY GDS

AI Architect

Brak informacji o wynagrodzeniu

SeniorHybryda·KatowiceFull-time

#466441·Dodano 9 dni temu·2

Źródło: nofluffjobs.com

Aplikuj teraz

Tech Stack / Keywords

AIMachine LearningData scienceDeep learning LLMs Python TensorFlow PyTorch LangChainHugging FaceRAGCloud platformAzure AWSData engineeringData modelingDegreeSecurityMLOpsDevOpsCloudCI/CD MLflow Git Kubernetes Docker Continuous deploymentEnterprise ArchitectContinuous integration

Podsumowanie oferty

Design and lead the implementation of enterprise AI solutions for clients, helping them apply data and AI technologies. Define AI strategies and architect scalable platforms using Generative AI, LLMs, Machine Learning, and cloud technologies.

Wymagania

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 AI frameworks such as TensorFlow, PyTorch, LangChain, and Hugging Face.
Understanding of retrieval-augmented generation (RAG), agentic AI systems, vector databases, and modern AI orchestration frameworks.
Experience with cloud platforms such as 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.

Nice to have:

Experience defining AI roadmaps, architecture standards, and governance frameworks for enterprise organizations.
Applying trusted AI practices to ensure fairness, transparency, accountability, security, and compliance in AI solutions.
Driving MLOps, LLMOps, and DevOps practices, including continuous integration, continuous deployment, monitoring, and model lifecycle management.
Using tools such as Docker, Kubernetes, Git, Azure AI Studio, MLflow, and CI/CD platforms to build and manage AI solutions.
Designing and implementing monitoring, observability, logging, and evaluation frameworks to support AI system reliability, performance, and responsible operation.
Collaborating with software engineering, cloud, security, and operations teams on AI solution deployment and integration.
Familiarity with enterprise architecture frameworks and security-by-design principles.
Experience leading technical teams, architecture reviews, and client-facing AI transformation initiatives.

Obowiązki

Design, govern, and lead the implementation of enterprise-grade AI solutions.
Work with business stakeholders, data scientists, engineers, and technology teams to define AI strategies, architect scalable platforms, and deliver solutions using Generative AI, LLMs, Machine Learning, NLP, MLOps, and cloud technologies.

EY GDS

40 aktywnych ofert

Zobacz wszystkie oferty

Aplikuj teraz