AI Engineer

  • Full Time
  • Development
  • Bucharest, Romania - Hybrid and remote-friendly

Overview

We’re looking for an AI Engineer to join one of our Data & AI teams. You’ll design, build, and deploy intelligent applications powered by Machine Learning, Large Language Models (LLMs), and Generative AI technologies. You’ll work closely with Data Scientists, Data Engineers, Solution Architects, and business stakeholders to transform business challenges into scalable AI solutions that deliver measurable impact.

Requirements

AI solution design & requirements

  • Collaborate with business stakeholders to understand business challenges and identify opportunities where AI can create measurable value.
  • Translate business requirements into scalable AI architectures and technical solutions.
  • Design end-to-end AI solutions integrating machine learning models, Large Language Models, enterprise data sources, and business applications.
  • Evaluate AI technologies and recommend the most appropriate approaches based on business and technical requirements.
  • Participate in technical workshops and solution design sessions with business and IT stakeholders.
  • Produce and maintain technical documentation, architecture diagrams, and AI solution specifications.

Generative AI & LLM development

  • Design, develop, and optimize applications powered by Large Language Models (LLMs).
  • Build Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources.
  • Develop prompt engineering strategies to improve model quality, reliability, and user experience.
  • Design and implement AI Agents capable of automating complex business workflows.
  • Integrate foundation models from platforms such as Azure OpenAI, OpenAI, Anthropic, Google Gemini, or open-source LLMs.
  • Evaluate AI models based on performance, latency, scalability, accuracy, and cost.

AI application development

  • Develop scalable backend services supporting AI-powered applications.
  • Integrate AI capabilities with enterprise applications through APIs and cloud services.
  • Design reusable AI components and orchestration workflows.
  • Collaborate with Data Engineers to build efficient AI data pipelines.
  • Develop secure, scalable, and maintainable production-ready AI solutions.
  • Contribute to software engineering best practices across AI projects.

MLOps & production deployment

  • Deploy AI applications into production environments.
  • Build and maintain CI/CD pipelines supporting AI and machine learning solutions.
  • Monitor AI application performance, usage, latency, and operational health.
  • Implement model versioning, deployment automation, and lifecycle management.
  • Support continuous model evaluation and improvement.
  • Contribute to AI governance, security, and responsible AI practices.

Testing, evaluation & continuous improvement

  • Design evaluation frameworks for AI applications and LLM-based solutions.
  • Validate AI outputs using quantitative and qualitative metrics.
  • Investigate production issues and optimize AI performance.
  • Reduce hallucinations and improve answer quality through prompt optimization, retrieval improvements, and evaluation.
  • Support User Acceptance Testing and production releases.
  • Contribute to reusable AI frameworks, coding standards, and engineering best practices.

Desired profile

Must-have

  • University degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, Mathematics, or a related field.
  • 3+ years of experience in AI Engineering, Machine Learning Engineering, Software Engineering, or Data Science.
  • Strong programming skills in Python.
  • Experience building applications using Large Language Models (LLMs).
  • Hands-on experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar.
  • Experience implementing Retrieval-Augmented Generation (RAG) architectures.
  • Understanding of embeddings, vector databases, semantic search, and prompt engineering.
  • Experience integrating AI services through REST APIs and cloud platforms.
  • Familiarity with Azure OpenAI, Azure AI Foundry, OpenAI API, AWS Bedrock, or Google Vertex AI.
  • Strong analytical, problem-solving, and communication skills.

Nice to have

  • Experience with AI Agents and agent orchestration frameworks.
  • Experience deploying AI solutions using Docker and Kubernetes.
  • Familiarity with MLflow, Azure ML, Databricks, or MLOps platforms.
  • Experience with vector databases such as Azure AI Search, Pinecone, Weaviate, Qdrant, or Milvus.
  • Experience with FastAPI, Flask, or backend application development.
  • Knowledge of cloud platforms (Microsoft Azure, AWS, or Google Cloud).
  • Experience in Banking, Retail, Insurance, or Telco industries.
  • Microsoft Azure AI Engineer, Databricks, AWS AI, or Google Cloud AI certifications.

How you work

  • Passionate about Artificial Intelligence and emerging technologies.
  • Curious, proactive, and continuously learning.
  • Comfortable working in multidisciplinary teams.
  • Strong ownership and attention to detail.
  • Focused on delivering scalable, secure, and production-ready AI solutions.
  • Committed to innovation, collaboration, and continuous improvement.
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