Senior Operations AI Engineer
Salary not listed • Athens • Full-time
Posted 1mo ago
About the job
We are seeking a Senior Operations AI Engineer to join our Procurement and Supply Chain team in Athens. This is a senior-level, hands-on technical leadership role for a passionate technologist with deep expertise in Machine Learning, Artificial Intelligence, and modern software engineering. You will architect AI systems that make operational decisions, sitting at the intersection of AI engineering and operational excellence. Your work will involve designing and delivering intelligent systems that autonomously monitor, reason, and optimize large-scale supply chain, logistics, and operations environments, acting as the go-to technical authority for your team and clients.
Responsibilities
- Build and deploy ML models using PyTorch, TensorFlow, and Scikit-learn for supply chain, logistics, and operations optimization.
- Develop agentic AI tools with LangChain, LangGraph, AutoGen, or CrewAI for autonomous monitoring, reasoning, and action recommendation.
- Design multi-agent systems with RAG pipelines, vector databases, and tool-calling architectures for end-to-end operational workflows.
- Deliver production-grade AI systems, including APIs, ML pipelines, and cloud deployments on Azure, AWS, or GCP using Docker and Kubernetes.
- Leverage AI coding tools like Cursor, Claude, and GitHub Copilot to accelerate development.
- Lead technical decision-making and advise the team on AI engineering.
- Stay updated on ML, GenAI, LLMs, MLOps, and Agentic Workflow trends, introducing new tools and patterns.
- Guide clients on AI adoption, feasibility, and implementation strategy for complex operational environments.
- Support business development through proposals, solution blueprints, and technical presentations.
- Mentor engineers, lead knowledge-sharing, and build AI capability within the firm.
- Present findings and recommendations to senior client leadership.
Requirements
- Degree in Computer Science, Electrical & Computer Engineering, Data Science, Mathematics, or a related field; PhD is a plus.
- 5-8 years of professional experience in production-based software engineering, ML engineering, AI systems, or data-intensive application development, with demonstrated technical leadership.
- Strong programming skills in Python, with proficiency in ML frameworks (PyTorch, TensorFlow, scikit-learn) and GenAI tooling (LangChain, LangGraph, or similar).
- Hands-on experience with agentic AI frameworks (AutoGen, CrewAI, or similar) and practical knowledge of LLMs, prompt engineering, RAG architectures, and AI orchestration.
- Proficiency with AI-assisted development environments (Cursor, Claude, GitHub Copilot, Windsurf, or similar).
- Solid understanding of databases, SQL, and data engineering concepts; experience with large-scale datasets or Apache Spark is a plus.
- Experience with cloud platforms (Azure preferred; AWS or GCP also valuable).
- Experience with data visualization tools (Power BI, Tableau).
- Excellent communication skills in Greek and English, with the ability to explain complex technical concepts to non-technical stakeholders.
- High adaptability to evolving requirements and dynamic project environments.
- Knowledge of supply chain, logistics, or operations domains is a strong advantage.
- Experience with multi-agent system design and autonomous workflow orchestration is a strong advantage.
- Familiarity with MLOps platforms (MLflow, Kubeflow, Azure ML) is a strong advantage.
- Experience designing and delivering end-to-end enterprise AI integrations (ERP, TMS, WMS) is a strong advantage.
- Strong curiosity and passion for continuous learning in the AI landscape is a strong advantage.