🇨🇿 Czechia · 17h ago
Expert AI Engineer
Ciklum Czech Republic & Slovakia
LinkedInseniorEnglish-friendly
Job DescriptionCiklum is looking for an Expert AI Engineer to join our team full-time in the Czech Republic.We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.About The RoleAs an Expert AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.ResponsibilitiesLead the design, development and deployment of advanced AI systems across Data Science and AI Engineering domainsArchitect and implement scalable AI pipelines and LLM-driven applications, including retrieval-augmented generation (RAG), orchestration and multi-agent systemsServe as the technical authority during client engagements, ensuring architecture quality, scalability, performance and reliabilityContribute hands-on to development activities, from experimentation and prototyping to production-grade implementationCollaborate with cross-functional engineering, data, and product teams to align technical solutions with client and business objectivesApply MLOps and LLMOps best practices for CI/CD, observability, evaluation and continuous improvement of AI models and pipelinesIntegrate AI services with enterprise platforms (e.g., Confluence, Jira, GitHub, CRM, ERP) and ensure seamless interoperabilityDrive innovation through internal frameworks and acceleratorsEnsure all AI solutions comply with security, data privacy and responsible-AI standardsMentor engineering peers and support knowledge sharing across teams and practices (e.g., contributing to Ciklum’s AI Academy)Commercial / PresalesAct as technical SME in presales conversations, translating business challenges into viable AI engineering solutionsPartner with delivery and account teams to shape long-term client engagement strategies based on engineering excellenceInternal Resource Management / Team Building And ManagementSupport recruitment efforts through technical assessments, interviews, and candidate evaluationMentor team members and contribute to cross-skilling initiatives within the AI and Engineering service linesUphold engineering excellence by promoting best practices, code quality, and delivery standards across projectsRequirementsWe know that sometimes, you can’t tick every box. We would still love to hear from you if you think you’re a good fit!General Technical Requirements8+ years of professional experience in software, data, or AI engineering, including at least 3–4 years of hands-on experience designing and implementing AI/ML solutionsBSc, MSc, or PhD in Computer Science, Mathematics, Engineering, or a related quantitative fieldDeep understanding of probability, statistics, and the mathematical foundations of machine learning and optimizationProven experience building and deploying advanced AI systems, including Large Language Models (LLMs), multimodal, and generative AI architecturesExposure to agentic system design, retrieval-augmented generation (RAG) and prompt engineering techniquesStrong proficiency in Python and common AI/ML development frameworks (e.g., PyTorch, TensorFlow, LangChain, Hugging Face or equivalent)Solid understanding of modern AI engineering practices, including model lifecycle management, observability, evaluation, versioning and continuous improvementFamiliarity with AI solution delivery methodologies (e.g., CRISP-ML(Q), TDSP or modern agile ML lifecycles)Ability to visualize, interpret, and communicate model outputs and insights effectively using modern tools and dashboardsSpecific Technical RequirementsProven experience in architecting and implementing end-to-end AI/ML solutions — from data ingestion and model training to deployment, monitoring and optimizationStrong software engineering skills for AI system development, including data processing, API integration, and model serving (Python, SQL and optionally Java/Scala or similar)Hands-on experience with cloud-native AI platforms and services (AWS SageMaker, Azure ML, GCP Vertex AI or NVIDIA AI stack)Proficiency in designing scalable ML/LLM pipelines and applying MLOps/LLMOps best practices (CI/CD, orchestration, monitoring, versioning, and deployment automation)Experience with diverse data modalities (structured, text, image, audio, video) and multimodal model integrationFamiliarity with handling complex data scenarios such as class imbalance, time-series forecasting and anomaly detectionUnderstanding of security, data governance and compliance considerations in AI system designDomain ExperienceBroad exposure to enterprise-scale AI solution design across industries such as BFSI, Healthcare, Aerospace, Manufacturing, Energy, Telecom or Technology sectorsProven ability to translate business and operational requirements into robust AI system architectures that deliver measurable impactFamiliarity with challenges of deploying AI in regulated environments and ensuring compliance with data privacy and protection frameworks (e.g., GDPR, CCPA, PCI DSS)Experience managing sensitive or high-value data (PII, PHI), implementing strong security, governance and access control mechanismsUnderstanding of enterprise data ecosystems and integration patterns (CRM, ERP, knowledge management or workflow systems)Business-related RequirementsProven experience delivering production-grade AI solutions that achieve measurable business and operational outcomesStrong ownership of the full AI engineering lifecycle — from problem framing and architecture design to deployment, optimization, and continuous improvementAbility to align technical decisions with business priorities, ensuring scalability, reliability, and measurable value from AI initiativesExcellent collaboration and communication skills to work effectively with cross-functional stakeholders, delivery teams, and clientsHigh degree of autonomy, accountability, and attention to detail in managing complex, multi-component AI systemsDesirableStrong background in software or solution architecture, ideally with previous experience as a Software or Data ArchitectProven ability to design scalable, distributed, and fault-tolerant AI architectures, integrating APIs, microservices, and event-driven componentsExperience with MLOps and LLMOps practices, including pipeline automation, containerization (Docker, Kubernetes), and continuous deployment of AI modelsDeep learning expertise using TensorFlow, PyTorch, or JAX, including fine-tuning and optimization of large modelsHands-on experience with Large Language Models (LLMs), Generative AI applications, and agentic or RAG-based systemsAdvanced SQL and familiarity with modern data platforms (Databricks, Snowflake, or equivalent)Experience with Big Data and streaming frameworks (Apache Spark, Kafka, Flink, etc.)Understanding of NoSQL and graph databases (e.g., Cassandra, Neo4j) and their role in AI knowledge managementExperience with cloud-native architectures and certified expertise in AWS, Azure, or GCP AI/ML servicesExposure to research or innovation projects, with publications or open-source contributions considered an advantageWhat's in it for you?Flexible working hoursHome office option5 weeks of holiday5 sick daysMultisport CardMeal allowanceInternal trainings including workshops and seminarsPaid certifications and technical as well as soft-skills trainingPossibility to participate in international conferencesFresh fruit, coffee, and a weekly company breakfast in the officeLoyalty bonus after 5, 10, 15 and more years with the companyReferral bonus programmeCorporate events including team building, outdoor activities, Christmas party, health week, summer ice cream, and moreHybrid and remote working options available across our Czech offices in Prague, Hradec Králové, and ZlínAbout UsAt Ciklum, we are always exploring innovations, empowering each Sourced from LinkedIn. 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