Senior AI Engineer

Role overview

Responsibilities

• check_circle Architect and build scalable, production-grade GenAI systems and services.
• check_circle Design and implement Retrieval-Augmented Generation (RAG) pipelines end-to-end.
• check_circle Integrate and orchestrate LLMs (OpenAI, Anthropic, Google, or open-source models) in real-world applications.
• check_circle Build internal abstractions, SDKs, and reusable components for GenAI capabilities.
• check_circle Implement evaluation pipelines, guardrails, and monitoring for hallucination detection, drift, and quality control.
• check_circle Optimize inference performance, cost, token usage, and response latency.
• check_circle Design multi-step agent workflows and tool integrations safely and reliably.
• check_circle Lead the transition from experimentation to hardened production systems.
• check_circle Mentor engineers and establish best practices for GenAI engineering.
• check_circle Line management responsibilities – 1-2 bright junior engineers.

Basic qualifications

• MSc in Computer Science, Engineering, or related STEM field (PhD is a plus).
• 4+ years of professional software engineering experience, with 1+ years building AI-powered systems in production.
• Strong backend engineering expertise: clean architecture, system design, SOLID principles, testing, and CI/CD.
• Deep experience building production-grade Agentic applications (not just prototypes or notebooks).
• Expert-level Python skills, including async programming, typing, packaging, and performance optimization.
• Experience designing scalable APIs and AI microservices (FastAPI or similar frameworks).
• Strong understanding of LLM system patterns: RAG, tool calling, agents, prompt orchestration, memory, and evaluation pipelines.
• Experience managing latency, cost, reliability, and fallback strategies in LLM-powered systems.
• Hands-on experience with cloud platforms (AWS or Azure), Docker, CI/CD pipelines, and infrastructure-as-code.
• Experience implementing monitoring, logging, tracing, and evaluation frameworks for GenAI systems.
• Experience with vector databases (Azure AI Search, PostgreSQL pgvector, Pinecone, FAISS, Weaviate, Qdrant).
• Strong communication skills and ability to lead technical discussions and mentor engineers.

Preferred qualifications

• Deep experience with LLM orchestration frameworks (LangChain, LlamaIndex).
• Experience hosting or fine-tuning open-source LLMs.
• Experience with model evaluation frameworks (RAGAS, custom eval harnesses, A/B testing for prompts).
• Experience building AI platforms or internal LLM gateways.
• Familiarity with distributed systems, message queues, or event-driven architectures.
• Experience with security, governance, and responsible AI practices in production environments.

Benefits

• check_circle Competitive salary and hybrid work model – come hang out in our Athens office or work remotely from anywhere in European economic Area (EU, Switzerland etc.) or UK (up to 6 weeks per year).
• check_circle Training budget to level up your skills from the top tech partners in the market (Microsoft, AWS, Salesforce, Databricks etc.) – whether it’s certifications or courses, we’ve got you covered.
• check_circle Private insurance, top-tier tech gear, and the chance to work with a stellar crew.