Senior AI Engineer-Romania

We are looking for an experienced Senior AI Engineer to design, develop, and deploy advanced AI solutions that solve complex business problems. The role combines software engineering expertise with practical experience in Machine Learning, Generative AI, Large Language Models (LLMs), and AI-powered applications.
The ideal candidate will work closely with data scientists, software engineers, product teams, and business stakeholders to transform AI concepts into scalable, reliable, and production-ready solutions.
Key Responsibilities
Design, develop, and deploy AI and Machine Learning solutions for real-world business use cases.
Develop and integrate Generative AI and LLM-based applications.
Design AI architectures covering data ingestion, model development, evaluation, deployment, and monitoring.
Build scalable AI services, APIs, and applications using modern software engineering practices.
Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) solutions.
Develop AI agents and intelligent workflows where appropriate.
Implement model evaluation, validation, monitoring, and continuous improvement processes.
Integrate AI capabilities into existing enterprise applications and cloud environments.
Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Owners, and business stakeholders.
Analyse complex business requirements and translate them into technical AI solutions.
Conduct experiments and proof-of-concepts to evaluate new AI technologies and approaches.
Optimise AI solutions for performance, scalability, reliability, cost, and latency.
Implement responsible AI practices, including security, privacy, governance, and monitoring.
Troubleshoot production issues and continuously improve the reliability of AI systems.
Contribute to technical architecture, code reviews, documentation, and engineering standards.
Stay up to date with emerging developments in AI, Generative AI, LLMs, and Machine Learning.
Must-Have Skills
5+ years of experience in software engineering, AI engineering, Machine Learning, or a related field.
Strong programming skills in Python.
Solid understanding of Machine Learning concepts, algorithms, and model lifecycle management.
Hands-on experience with Generative AI and Large Language Models (LLMs).
Practical experience with RAG architectures, embeddings, vector databases, and semantic search.
Experience with prompt engineering and LLM evaluation.
Experience developing and consuming REST APIs and AI/ML services.
Strong knowledge of software engineering principles, clean code, testing, version control, and CI/CD.
Experience with at least one major cloud platform such as Azure, AWS, or Google Cloud.
Experience with AI/ML frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn, or Hugging Face.
Experience working with data processing and integration pipelines.
Understanding of MLOps / LLMOps concepts, including deployment, monitoring, evaluation, and model lifecycle management.
Strong analytical and problem-solving skills.
Ability to communicate complex AI concepts clearly to both technical and non-technical stakeholders.
Strong English communication skills.
Nice-to-Have / Advantages
Experience building AI agents and multi-agent systems.
Experience with agentic AI frameworks such as LangChain, LangGraph, Semantic Kernel, or similar technologies.
Experience with Azure OpenAI, Amazon Bedrock, Google Vertex AI, or other managed AI platforms.
Knowledge of MCP (Model Context Protocol) and tool-based AI integrations.
Experience with fine-tuning, RAG optimisation, or model adaptation techniques.
Experience with vector databases such as Azure AI Search, Pinecone, Weaviate, Milvus, or pgvector.
Knowledge of Docker and Kubernetes.
Experience implementing AI observability, including latency, cost, hallucination, quality, and drift monitoring.
Knowledge of AI security, privacy, governance, and responsible AI practices.
Experience with GenAI evaluation frameworks and automated testing.
Familiarity with data platforms such as Databricks, Snowflake, or BigQuery.
Experience working in Agile/Scrum environments.
Previous experience leading technical initiatives or mentoring other engineers.
Relevant certifications in AI, Machine Learning, or Cloud technologies.

Work arrangement
Yes