AI Engineer, 4+ years experience

General

We are looking for AI Engineers to build secure, scalable AI solutions that solve real business problems and run reliably in production across various industries.

 

Responsibilities/Activities

• Work with business and technical teams to identify valuable AI use cases and turn them into practical, measurable solutions
• Design, build and deploy end-to-end Generative AI applications, assistants and AI agents used in real production environments
• Create agentic and multi-step workflows with tool calling, structured reasoning and secure access to internal services, APIs and data sources
• Build and improve RAG pipelines, including document processing, embeddings, vector search, retrieval, re-ranking, grounding and context management
• Integrate commercial and open-source LLMs, selecting the right model for each use case based on quality, latency, security and cost
• Develop production-ready backend services and APIs, mainly in Python, and integrate AI components with enterprise platforms and applications
• Prepare, clean, structure and validate both structured and unstructured data used by AI solutions
• Design evaluation and testing approaches for AI outputs, including automated quality checks, hallucination reduction, safety validation and model comparison
• Implement monitoring, logging, alerting and cost controls, and continuously improve accuracy, performance, reliability and user experience
• Apply security, privacy, access-control and responsible-AI practices throughout the solution lifecycle
• Containerize and deploy applications through cloud platforms and CI/CD pipelines, supporting stable operation and continuous delivery
• Document architecture, technical decisions, testing results and support procedures, and share knowledge with technical and non-technical stakeholders
• Troubleshoot issues across models, prompts, APIs, data flows, infrastructure and application components

Requirements

Technical

• At least 4 years of previous experience in AI Engineering, Machine Learning Engineering, Data Engineering or related roles
• Hands-on experience building and deploying Generative AI or LLM-based solutions beyond proof-of-concept stage
• Strong Python skills and experience building maintainable, production-grade services, APIs and integrations
• Practical experience with LLM APIs or platforms such as Azure OpenAI, OpenAI, Anthropic, AWS Bedrock, Google Vertex AI or similar
• Experience with prompt engineering, function/tool calling, AI agents, multi-step workflows and model orchestration
• Experience with automated LLM evaluation, LLM-as-a-judge, prompt/version testing or evaluation-driven development
• Experience designing and optimizing RAG solutions using embeddings, semantic search and vector databases
• Experience with asynchronous Python, FastAPI, event-driven systems, streaming APIs or low-latency architectures
• Good understanding of REST APIs, webhooks, authentication and integration patterns for enterprise applications
• Experience with SQL and with preparing, transforming and validating structured and unstructured data
• Solid software engineering fundamentals, including modular design, scalability, maintainability, testing, version control and debugging
• Experience with Git, Docker and CI/CD practices, plus working knowledge of at least one cloud platform: Azure, AWS or GCP
• Ability to evaluate AI solutions using quality, accuracy, latency, safety, reliability and cost metrics
• Understanding of secure AI integration, data privacy, access control, auditability and responsible-AI principles

Education

• University degree in Computer Science, Data Science, Artificial Intelligence or another related field

Others

• Good level of English (oral and written)
• Strong problem-solving mindset and a hands-on approach to turning unclear business needs into reliable technical solutions
• Clear communication skills and the ability to work effectively with engineers, data specialists, business stakeholders, and external partners
• Curiosity, ownership and willingness to learn in a fast-moving technology area

Nice to have requirements

• Experience with MLOps, LLMOps or AIOps, model lifecycle management and production observability
• Experience with PyTorch, TensorFlow, JAX, Spark, Databricks or classical machine-learning workloads
• Experience with Java, .NET, JavaScript/TypeScript, React or Vue for wider application integration
• Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel or agent SDKs
• Knowledge of Model Context Protocol (MCP), multi-agent systems or AI-to-AI collaboration patterns
• Knowledge of OAuth2, OIDC, SSO and enterprise authentication patterns
• Experience with speech-to-speech, multimodal AI, computer vision or real-time conversational systems
• Contributions to open-source AI projects, technical publications, patents or internal AI standards
• Experience in regulated or large enterprise environments