AI Visionary

3 days ago

Dublin, Dublin City, Ireland beBeeArtificial Full time €180,000 - €200,000

Transform your career in AI Platform Engineering as a visionary Staff Software Engineer.

About the Role

We're seeking a seasoned expert to build the intelligent core of our AI platform by engineering autonomous agents that perceive, reason, and learn in complex environments.

  • Create adaptive systems that operate in real-world conditions using agentic design, LLMs, knowledge graphs, and reasoning engines.
Key Responsibilities

You'll be responsible for:

  • Designing and implementing autonomous AI agents capable of perception, reasoning, and learning in complex, real-world environments
  • Developing and optimizing agentic architectures using LLMs, vector databases, and symbolic reasoning engines
  • Applying advanced RAG techniques, prompt engineering, and fine-tuning to enhance agent performance
  • Integrating knowledge graphs and multi-modal capabilities to enable contextual and adaptive agent behavior
  • Building robust evaluation frameworks, A/B testing pipelines, and model versioning systems
  • Collaborating with platform, data, and product teams to ensure seamless deployment and continuous improvement of intelligent agents
Requirements

To succeed in this role, you'll need:

  • 5-7+ years of experience in applied AI/ML, with a strong focus on building intelligent systems and autonomous agents
  • Deep expertise in Python and/or TypeScript
  • Hands-on experience with multiple LLMs (e.g., GPT, Llama, Claude, Gemini), including fine-tuning, advanced RAG techniques, and prompt engineering
  • Proficiency with agent frameworks such as LangChain, LangGraph, AutoGen, or CrewAI
  • Experience developing agent planning and reasoning algorithms (e.g., Tree of Thoughts, ReAct, Monte Carlo Tree Search)
  • Strong background in model evaluation, A/B testing, and versioning for AI models
  • Familiarity with vector databases (e.g., Pinecone, Milvus, Chroma)
  • Experience with knowledge graphs (e.g., Neo4j, RDF) and symbolic AI approaches
  • Understanding of multi-modal LLM capabilities and responsible AI practices
  • Experience with explainable AI (XAI) and responsible AI toolkits
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
  • Preferred: PhD in AI, Cognitive Science, or a related discipline
  • Certifications in AI/ML (e.g., DeepLearning.AI, Google Cloud ML Engineer) are a plus

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