Senior AI Engineer

Greece·AthensFull-timesenior

Machine Learning EngineerData

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Quick Summary

Key Responsibilities

Build production-grade GenAI applications: Design and develop AI-powered services and applications using Python,

Requirements Summary

Guide engineering decisions, review designs and code, mentor other engineers and establish best practices for building GenAI applications. Stay ahead: Explore emerging GenAI technologies,

Technical Tools

Machine Learning EngineerData

Build production-grade GenAI applications: Design and develop AI-powered services and applications using Python, LLMs and modern software engineering practices—from prototypes to scalable production systems.
Engineer intelligent workflows: Build RAG pipelines, AI agents, tool-calling workflows, structured generation, conversational systems and other LLM-powered capabilities that solve real business problems.
Own the software behind the AI: Develop clean, modular and testable backend services, APIs and integrations, ensuring AI solutions are scalable, maintainable and production-ready.
Design AI architectures: Make architectural decisions around model selection, orchestration, retrieval, APIs, caching, data stores, vector databases and cloud infrastructure.
Make AI reliable: Implement evaluation frameworks, observability, tracing, monitoring and guardrails to understand how AI systems behave and continuously improve their quality.
Optimize performance: Improve latency, throughput, reliability and cost across LLM-powered applications through model routing, caching, asynchronous processing and thoughtful system design.
Integrate the AI ecosystem: Work with foundation models and platforms from providers such as OpenAI, Anthropic, Google, Microsoft and open-source ecosystems.
Collaborate across disciplines: Work closely with Software Engineers, Data Engineers, Data Scientists, Product teams and domain experts to translate business requirements into effective AI products.
Lead technically: Guide engineering decisions, review designs and code, mentor other engineers and establish best practices for building GenAI applications.
Stay ahead: Explore emerging GenAI technologies, frameworks and architectural patterns and assess where they can create meaningful value rather than adopting technology for technology's sake.
Document and share: Create clear technical documentation, architectural decisions and reusable patterns that help the broader team build better AI systems.

Requirements

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Degree in Computer Science, Software Engineering, STEM or equivalent practical experience.
5+ years of professional software engineering experience, ideally building backend, cloud-native or data-intensive applications, including 1+ year in building GenAI systems.
Strong experience designing and developing production systems using Python.
Solid understanding of software engineering fundamentals, including clean architecture, design patterns, testing, API design, concurrency, asynchronous programming and maintainable codebases.
Hands-on experience building applications with Large Language Models and Generative AI, including areas such as:

Retrieval-Augmented Generation (RAG)
Agentic workflows and tool/function calling
Αgent orchestration, multi-agent systems, MCP or tool-based AI architectures.
Prompt engineering and structured outputs
Embeddings and semantic search
Context and conversation management
LLM evaluation and observability
Guardrails and responsible AI patterns

Experience with frameworks and libraries such as FastAPI, Pydantic and at least one GenAI orchestration ecosystem such as LangChain, LangGraph, LlamaIndex or Semantic Kernel.
Experience working with mainstream AI platforms and foundation models from OpenAI, Azure OpenAI, Anthropic, Google and/or open-source model providers.
Experience with vector databases and search technologies, such as Azure AI Search, Elasticsearch/OpenSearch, pgvector, Pinecone, Weaviate, Qdrant or similar.
Strong understanding of REST APIs, distributed systems and service-oriented architectures.
Hands-on experience with at least one major cloud platform such as Azure or AWS.
Experience writing automated tests and building reliable engineering workflows.
Ability to reason about trade-offs between model quality, latency, scalability, security and cost.
Fluent English and strong communication skills, with the ability to explain complex technical decisions clearly to both technical and non-technical stakeholders

What We Offer

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✓Competitive Salary – A rewarding package that reflects your skills and experience.

✓Flexible Working –Enjoy flexible hybrid model in our modern Athens office or work remotely from anywhere in European economic Area (EU, Switzerland etc.) or UK (up to 6 weeks per year).

✓Health & Wellness Benefits – Private insurance, and the chance to work with a stellar crew.

✓Learning & Development –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.

✓Career Growth – Clear opportunities to develop your skills and progress within the company.

✓Great Team & Culture – Work with talented, supportive people in a collaborative environment.

✓Team Events & Perks – Enjoy social events, celebrations, and exclusive employee benefits.

✓Modern Tools & Technology – Everything you need to do your best work.

✓A Workplace That Values You – Your ideas, contribution, and well-being genuinely matter