Top Artificial Intelligence Jobs in Czechia

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Design, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.

Lead design, development, and deployment of scalable AI/LLM systems (RAG, multimodal, agentic). Architect end-to-end ML pipelines, apply MLOps/LLMOps, integrate with enterprise platforms, ensure security/compliance, support presales, mentor teams, and drive AI innovation and delivery.

Join the MLOps team to deploy, maintain, and monitor ML models in production. Build data and model pipelines, implement CI/CD for ML, optimize performance and cost, and collaborate with cross-functional teams to ensure scalable, reliable AI solutions.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

Lead design and architectural direction for generative AI, LLM, RAG, and intelligent automation solutions. Collaborate with architects, engineers, product owners, and stakeholders to ensure secure, scalable cloud solutions aligned with enterprise standards. Provide technical leadership, make strategic architecture decisions, and mentor AI engineers across the organization.

Design and scale end-to-end AI/ML solution patterns, data pipelines, and model architectures; lead pilot MVPs/PoCs into production; define AI governance and best practices; collaborate with architects, engineering, and sales to drive services growth.

Design, build, and deploy production LLM systems and workflows for search, analytics, reasoning, and automation. Lead fine-tuning, training pipelines, model optimization, deployment, monitoring, and continuous improvement while translating business needs into scalable LLM architectures.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

Build production systems that let AI agents safely author code changes inside deterministic gates with verification and auditable trails. Own end-to-end features, design trust boundaries and least-privilege models, implement evaluation and observability for non-deterministic systems, and collaborate with security and platform teams to meet compliance and audit requirements.

Lead design and governance of ICON's end-to-end AI platform, multi-agent frameworks, and supporting services. Define cloud-native, scalable architectures, integration patterns, APIs, and standards; lead solution architecture, design reviews, and mentor engineering teams to deliver secure, high-performing AI/ML production systems.

Join a cross-functional team to design and implement AI agents and LLM-powered applications. Use GitHub Copilot and AI-assisted development, apply prompt engineering, integrate tools and agent workflows, and leverage technical documentation as knowledge sources. Deliver PoC work and contribute to SDLC improvements and best practices.

Develop tools and libraries in Python for neural network optimization, contribute to open-source projects, and enable AI technologies on devices.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Build ShipMonk's AI domain: consult with stakeholders to identify real problems, design and implement AI/ML projects from prototype to production, make AI tools accessible to non-technical teams, and balance technical complexity with business impact.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The role involves data collection, evaluation, comparison, and annotation to enhance AI-generated content in Vietnamese, ideal for flexible workers.

Create short- and long-form AI-generated educational and entertainment content for Instagram, TikTok, and YouTube. Rapidly test content hypotheses, analyze performance, research trends and competitors, and iterate on hooks, storytelling, and editing. Collaborate with the product team and continually experiment with AI image/video generation and editing tools.

As a Senior AI Engineer, you will shape the AI strategy for a fintech compliance platform, design scalable machine learning models, and mentor an AI team while ensuring model compliance and ethics.

As a Senior Software Engineer in AI, you'll build and maintain ML features, collaborate with data scientists, and ensure quality and performance in a production environment within a SaaS setup.