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Senior AI Engineer

Hybrid in Romania
AI Engineering
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We are looking for a skilled and innovation-driven AI Engineer to join our team and spearhead the development of cutting-edge generative AI solutions.

If you're passionate about artificial intelligence and adept at building systems that deliver measurable business impact, this opportunity is ideal for you. Work with a dynamic group of professionals to create and deploy AI-driven technologies that tackle real-world challenges while working in a collaborative and forward-focused environment.

Responsibilities
  • Design, implement and maintain end-to-end AI applications, including chatbots, Q&A platforms and agent workflows
  • Collaborate directly with clients to understand their needs, identify opportunities and recommend LLM-driven solutions
  • Develop and manage robust data pipelines, prompt strategies and datasets to ensure effective and accurate AI models
  • Evaluate and refine AI system performance, ensuring outputs are accurate, secure, scalable and compliant with industry regulations
  • Conduct research and rapid prototyping to validate technical feasibility and demonstrate the business value of AI solutions
  • Stay current with evolving LLM technologies, frameworks and methodologies to continuously improve solutions and client outcomes
Requirements
  • Strong proficiency in Python, experience with web frameworks like FastAPI or similar
  • Understanding of the AI application development lifecycle
  • Experience with rapid UI prototyping using Streamlit, Gradio or similar frameworks
  • Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (LangGraph, LlamaIndex, Strands Agents, etc.)
  • Knowledge of advanced AI integration patterns (e.g., RAG, Agents)
  • Experience deploying AI solutions at scale with considerations for performance, cost-efficiency and maintainability
  • Proven ability to evaluate generative AI quality using metrics such as retrieval and classification scores, as well as LLM-based evaluation methods
  • Proven experience in AI engineering and delivering ML-based solutions
  • Strong problem-solving skills and attention to detail
  • Excellent communication, collaboration and interpersonal skills
Nice to have
  • Experience designing experiments, conducting A/B tests and iterating on models based on user feedback
  • Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
  • Familiarity with emerging protocols such as MCP, A2A, ACP, etc.
  • Experience deploying to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (e.g., vLLM)
  • Experience with enterprise AI platforms such as AWS AgentCore, Databricks AgentBricks, Google Agents Space or Azure AI Foundry
  • Experience with observability and monitoring tools and frameworks
Technologies
  • Python, PyTorch, Hugging Face, LangChain
  • Vector databases, including Qdrant, FAISS, Chroma
  • APIs for LLMs such as Azure OpenAI and AWS Bedrock