Senior Staff AI Engineer (Knowledge Graph)

Generative AI Solutions: 
• Build AI-powered applications, AI agents, and Copilot experiences using Large Language Models (LLMs) and modern AI technologies.
• Design and optimize LLM-based solutions, including prompt engineering, tool/function calling, Retrieval-Augmented Generation (RAG), GraphRAG, and agentic workflows.
• Design, develop, and integrate knowledge graph and graph database solutions (e.g., Neo4j, Cosmos DB) to model complex business relationships, enhance contextual understanding, and improve AI reasoning capabilities.
• Evaluate, fine-tune, and improve AI systems through structured testing, quality measurement, safety guardrails, and hallucination reduction techniques.

Machine Learning Models:
• Design and implementation of machine learning models  in different domains (e.g. SCM, Manufacturing, Product Management and Corporate Functions) following the CRISP-    DM process.
• Train, fine-tune, and optimize deep learning models for various applications.
• Work with large-scale datasets to preprocess, clean, and transform data for model training.

Data Pipelines & ML Model Deployment:
• Design and build robust data pipelines for AI applications.
• Collaborate with data engineers to optimize data infrastructure and storage for efficient ML processing.
• Deploy and monitor models in production environments.

Communication & Collaboration:
• Storytelling of results to business stakeholder.
• Collaborate with business stakeholders, architects, data engineers, and software developers to transform business challenges into scalable AI solutions.

Stay updated:
• Stay updated with the latest trends and advancements in data science and AI.

• Master's degree in Computer Science, Math, Statistics, Data Science, Artificial Intelligence or a related field.
• Over 7 years of experience in implementing machine learning solutions using Python, R, or similar languages, with extensive knowledge of various ML algorithms.
• Strong expertise in Generative AI, including Large Language Models (LLMs), Knowledge Graphs, AI Agents, prompt engineering, model evaluation, and responsible AI.
• 7+ years of hands-on experience in Data Science, Machine Learning, LLMs and AI.
• Deep understanding of Retrieval-Augmented Generation (RAG) architectures, including embeddings, vector databases, semantic search, and retrieval optimization techniques.
• Knowledge of Knowledge Graphs, semantic data models, ontologies, graph databases (e.g., Neo4j), and their application in enterprise AI solutions.
• Experience with GraphRAG and hybrid retrieval approaches combining vector search and knowledge graphs to improve AI accuracy, explainability, and contextual understanding.
• Hands-on experience with cloud-based AI services such as Azure OpenAI, Azure AI Foundry, Azure AI Search, or comparable platforms.
• Knowledge of MLOps and LLMOps, including model deployment, monitoring, evaluation, version control, testing, and governance.
• Excellent communication and stakeholder management skills.
• Strong interpersonal and collaborative skills.

1. Global Collaboration Opportunities on New Exciting Projects 
2. Flexible and Hybrid Working Mode 
3. Diversified, Rewarding & Supportive Workplace