Senior AI Architect

Cloud Architecture & AI Integration Consulting:

• Providing guidance on the design and integration of cloud infrastructures (Azure, AWS) and AI technologies

Architecture Development:

• Designing and implementing scalable Data & AI architectures, driving the development of modern AI infrastructures.

Pipeline & MLOps Engineering:

• Collaborating with AI engineers and data scientists to build robust data pipelines, optimize MLOps/LLMOps workflows, and ensure smooth model deployment.

Governance & IT Security:

• Ensuring data quality, security, and compliance through data governance frameworks, system hardening, encryption, access control, and alignment with data protection regulations.

Mentoring & Team Development:

• Supporting the team in developing expertise in AI architecture through technical mentoring, knowledge sharing and leadership

Innovation:

• Monitoring current and future trends and advancements in AI, machine learning, and other emerging technologies.

Implement cost monitoring and usage tracking of AI workloads across cloud platforms to ensure responsible and efficient resource consumption.

• Master’s degree in Computer Science, Data Science, or related field.
• 5+ years in AI/ML solution architecture.
• Proven experience in AI related projects from concept to deployment.
• Expertise in cloud technologies (AWS, Azure, GCP, MS Fabric), AI/ML models, MLOps, data pipelines (e.g., Spark, Kafka), and modern architecture patterns (e.g. Data Mesh, Lakehouse).
• Deep hands-on experience with both traditional machine learning (e.g., regression, classification, clustering) and generative AI (e.g., transformers, LLMs, prompt engineering), using frameworks like Scikit-learn, TensorFlow, and PyTorch.
• Proficient in Azure AI services (Azure AI Foundry, Cognitive Services, Azure ML), MLOps practices (CI/CD for ML, model deployment, monitoring), and scalable data processing with tools like Spark, Azure Data Lake, and Kubernetes.
• Strong understanding of responsible AI principles (fairness, explainability, compliance), with a proven ability to align AI solutions to business needs and collaborate across engineering, product, and domain teams.
• Strong analytical and problem-solving skills; Agile Methods (SCRUM, SAFe).
• Experience in technical leadership roles & working in an international team.
• Excellent communication in English language and stakeholder management skills.