AI Engineer

• Assist in developing and maintaining user-facing features using Angular and TypeScript
• Build and debug backend services with Node.js, under guidance from medior/senior team members
• Test, document, and support new software features
• Learn to use AI productivity tools (e.g., code assistants, AI-assisted code review/test generation) as part of your workflow
• Participate in code reviews and Agile ceremonies, contributing to team discussions and learning best practices
• Integrate with internal/external APIs and enterprise platforms with supervision

Junior Full-Stack Developer, AI-Native Mindset

• Architect, deliver, and maintain high-quality front-end (Angular/TypeScript) and backend (Node.js) solutions for critical internal tools and dashboards
• Lead integration with complex enterprise APIs and systems (e.g., GitHub, Jira, monitoring, Kubernetes)
• Champion the use of AI development tools and best practices (automated refactoring, test generation, code review) to maximize delivery velocity and code quality
• Set and reinforce engineering standards—design, testing, security, maintainability, and operational excellence
• Coach and mentor junior and medior developers; facilitate code reviews and guide team technical growth
• Collaborate closely with stakeholders to translate operational needs into scalable, production software
• Drive continuous improvement across CI/CD, monitoring, operational automation, and documentation

Senior Full-Stack Developer, AI-Native Mindset

• Owns:
• Design, deploy, monitor, and evaluate customer-facing AI agents that improve the shopping experience and proactively assist users.
• The design, maintenance, and deployment of autonomous AI agents that can reason, plan, and execute complex business processes. Experience with human-in-the-loop processes.
• Special focus is on Voice technologies: We design AI systems capable of real-time interaction with spoken user input.
• The full software development cycle — from building solutions to creating robust CI/CD pipelines and monitoring.
• The implementation of comprehensive observability and monitoring for all AI systems.
• Establishing rigorous evaluation frameworks to ensure systems meet the highest standards of quality, reliability, and meaningful guardrails.
• Partners with:
• Technical and non-technical stakeholders to deliver practical solutions that drive business value.
• Supports:
• The cost-efficiency of our AI systems by proactively implementing strategies like intelligent model routing, caching, and prompt optimization.

Machine Learning Engineer

• Owns the development and maintenance of specific features and components within our ML services.
• Contributes to the development and fine-tuning of our predictive engines, including models for forecasting, planning, and process optimization.
• The full MLOps lifecycle for business-critical ML services, including building robust CI/CD pipelines and implementing comprehensive observability and monitoring.
• Partners with business and product leaders to identify high-impact use cases for machine learning and AI.
• Provides input to actionable business improvements by translating complex algorithms and data insights into pragmatic solutions.
• Supports the automation of decisions and minimization of manual intervention in core business processes through the use of AI and machine learning.
• The continuous enhancement of our business capabilities by proactively exploring and experimenting with new ML/AI trends.

• Design and develop scalable data pipelines, backend services, and APIs.
• Build knowledge graph solutions, including graph data modeling, relationship mapping, and graph traversal logic.
• Build ETL pipelines.
• Design data models.
• Implement GraphRAG solutions combining knowledge graphs, vector search, metadata, and LLM-based retrieval.
• Create Source to Target Mappings (STMs) for ETL specifications.
• Implement automated ingestion patterns, incremental (delta) updates, and streaming/CDC workflows.
• Gather requirements, set targets, define interface specifications, and conduct design sessions.
• Work closely with data consumers to ensure proper integration.
• Adapt and learn in a fast-paced project environment.

Machine Learning Engineer jobs in Czechia

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Junior Full-Stack Developer, AI-Native Mindset

Senior Full-Stack Developer, AI-Native Mindset

AI Engineer

Machine Learning Engineer

Senior AI Engineer, GraphRAG, Neo4J