AI Cloud Architect

Responsibilities:

• Building high-performing, scalable, enterprise-grade LLM/AI applications in cloud environment
• Working with Data Science teams to analyze requirements, build architecture conceptions, lead a implementation GenerativeAI and Machine Learning models into production (Tech Lead)
• Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency
• Design, delivery and management of industrialized processing pipelines
• Defining and implementing best practices in GenAI/ML models life cycle and ML operations/LLM operations
• Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices
• Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations
• Gathering technical requirements & estimating planned work
• Presenting solutions, concepts and results to internal and external clients
• Creating technical documentation including diagrams

Requirements:

• At least 8+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.)
• At least 8+ years of experience in production-ready ML-related code development
• At least 2 years of experience in production-ready LLM-related code development, preferably based on the Retrieval Augmented Generation concept (RAG)
• At least 3+ years of experience in Cloud Architecture
• Good understanding and experience with GenerativeAI models APIs (Large Language Models/Large Multimodal Models)
• Good understanding and experience with LLM orchestrators (e.g., Langchain, etc.) and concepts (RAG, in-context learning, fine-tuning)
• Good understanding of LLM evaluators, validators, and guardrails
• Good understanding of LLMOps concepts like GenAI operationalization\scaling (e.g., LLMs serving, performance & API Gateways, LLMs tracking & monitoring)
• Experience in developing GenAI apps in rapid frameworks (e.g., Streamlit)
• Experience in MLOps/LLMOps tools like AzureML/AzureAI or GCP VertexAI
• Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures
• Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP
• Knowledge of UML notation
• Good communication skills and ability to work in a team and support others
• Fluency in written and spoken English
• Taking responsibility for tasks, deliverables and great problem-solving skills, critical thinking

Nice to have:

• Experience in designing, programming ML algorithms, and data processing pipelines using Python 
• Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps) 
• Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes 
• Knowledge of BPMN, Archimate 

Offer:

• Private medical care
• Co-financing for the sport card
• Training & learning opportunities