Senior AI Solutions Engineer

Location: Athens, Greece

Company

Provides clinical research services, commercial insights, and healthcare intelligence for life sciences and healthcare organizations.

What you will do

• Design, develop, evaluate, and deploy AI, machine learning, GenAI, and agentic AI solutions for complex business and client challenges.
• Translate business requirements into scalable technical solutions and implementation plans.
• Build intelligent workflows using machine learning models, LLMs, enterprise data, APIs, and agentic frameworks, including RAG, semantic search, knowledge discovery, intelligent automation, and decision support.
• Define evaluation approaches covering solution quality, performance, business impact, and risk.
• Integrate AI solutions with enterprise platforms, data sources, analytical products, APIs, and cloud platforms.
• Partner with business, analytics, data science, and technology stakeholders to move proofs of concept into reusable, production-ready capabilities and support adoption across markets and business units.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Experience designing and deploying AI, machine learning, advanced analytics, or GenAI solutions in production environments.
• Strong understanding of AI, machine learning, Generative AI, LLMs, prompt engineering, and agentic AI concepts.
• Experience building solutions with modern AI frameworks and tools, and knowledge of RAG, vector databases, semantic search, and knowledge retrieval techniques.
• Experience integrating AI solutions with enterprise systems, APIs, and cloud platforms.
• Strong software engineering and solution development skills.
• Understanding of AI governance, evaluation, monitoring, security, and compliance practices.
• Ability to communicate technical concepts to technical and non-technical stakeholders.

Nice to have

• Experience building AI-powered products or client-facing AI solutions.
• Familiarity with orchestration frameworks, AI agents, and multi-agent systems.
• Experience with structured and unstructured enterprise data.
• Knowledge of predictive analytics, machine learning, and advanced analytics methodologies.
• Knowledge of Responsible AI, model governance, compliance, and risk management.
• Experience in healthcare, life sciences, commercial analytics, or consulting environments.
• Familiarity with MLOps and LLMOps practices.

Culture & Benefits

• Focus on applying AI technologies to real-world business challenges.
• Builder's mindset centered on moving from concept to deployment.
• Continuous learning and curiosity about emerging technologies.
• Strong collaboration and stakeholder management.
• Focus on practical, scalable, and measurable business outcomes.