AI Engineering Lead

Description

The team is in Greece and works on the Analytics & AI team, turning ideas into scalable, secure and human-centred technology for clients and internal projects.

The role is a principal technical specialist position that combines hands-on AI delivery, engineering quality, business development support and technical leadership.

Responsibilities

• Work with business stakeholders to understand their needs and design AI-infused solutions for real business problems.
• Lead the architecture and delivery of end-to-end AI systems, covering ML models, LLM-based components, APIs and scalable cloud deployments.
• Make technical decisions and serve as the main engineering advisor to the team.
• Coach the AI engineering team as they build their DevOps skills, and make sure they follow best practices across the SDLC.
• Write production-grade code that is high quality, scalable, maintainable and built with modern engineering practices.
• Connect AI components to enterprise applications, data sources and third-party systems.
• Enforce DevOps and MLOps practices, including CI/CD, observability, testing and cloud-native workflows.
• Track market trends and new technologies in ML, GenAI, LLMs, MLOps, agentic workflows, software engineering and cloud platforms.
• Bring in new tools, frameworks and patterns that strengthen AI delivery.
• Advise internal teams and clients on AI adoption, feasibility, risks and implementation strategy.
• Help with business development by contributing to proposals, solution blueprints and technical presentations.
• Spot opportunities where advanced analytics and AI can create value for clients.
• Mentor junior engineers and take part in the wider the company engineering community.
• Lead knowledge-sharing initiatives and help build capability across the firm.

Requirements

• A degree in computer science, electrical and computer engineering, or a related field. A PhD is a plus.
• More than 6 years of professional experience in production software engineering, ML engineering, AI systems, AI engineering or data-intensive application development.
• A record of technical leadership or of owning complex systems.
• Strong programming skills in Python (preferred),.NET, Java or similar languages.
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow or Scikit-learn, and with GenAI tooling such as LangChain, LangGraph or similar orchestration frameworks.
• A solid grasp of databases, SQL and data engineering. Experience with large-scale datasets or Apache Spark is a plus.
• Experience with cloud platforms. Azure is preferred; AWS or GCP is also valuable.
• The ability to design scalable, secure and resilient systems using DevOps and cloud-native practices.
• Clear communication, including explaining complex ideas to non-technical stakeholders.
• Adaptability to changing requirements and fast-moving projects.
• A strong curiosity and a drive to keep learning in the fast-changing AI field.

Conditions

Hybrid working model.

Collaborative office spaces.

Equal-opportunity statement: all applicants will be acknowledged and treated in the strictest confidentiality.

Benefits

• Local and global career opportunities.
• Continuous learning and professional certifications.
• Extra leave days and wellness initiatives.
• An inclusive team where your contribution is valued.