[Hiring] Expert AI Engineer @Ciklum

Role Description

Ciklum is looking for an Expert AI Engineer to join our team full-time in Poland. As an Expert AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.

Responsibilities:

• Lead the design, development and deployment of advanced AI systems across Data Science and AI Engineering domains
• Architect and implement scalable AI pipelines and LLM-driven applications, including retrieval-augmented generation (RAG), orchestration and multi-agent systems
• Serve as the technical authority during client engagements, ensuring architecture quality, scalability, performance and reliability
• Contribute hands-on to development activities, from experimentation and prototyping to production-grade implementation
• Collaborate with cross-functional engineering, data, and product teams to align technical solutions with client and business objectives
• Apply MLOps and LLMOps best practices for CI/CD, observability, evaluation and continuous improvement of AI models and pipelines
• Integrate AI services with enterprise platforms (e.g., Confluence, Jira, GitHub, CRM, ERP) and ensure seamless interoperability
• Drive innovation through internal frameworks and accelerators
• Ensure all AI solutions comply with security, data privacy and responsible-AI standards
• Mentor engineering peers and support knowledge sharing across teams and practices (e.g., contributing to Ciklum’s AI Academy)

Commercial / Presales:

• Act as technical SME in presales conversations, translating business challenges into viable AI engineering solutions
• Partner with delivery and account teams to shape long-term client engagement strategies based on engineering excellence

Internal resource management / team building and management:

• Support recruitment efforts through technical assessments, interviews, and candidate evaluation
• Mentor team members and contribute to cross-skilling initiatives within the AI and Engineering service lines
• Uphold engineering excellence by promoting best practices, code quality, and delivery standards across projects

Qualifications

• 8+ 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 solutions
• BSc, MSc, or PhD in Computer Science, Mathematics, Engineering, or a related quantitative field
• Deep understanding of probability, statistics, and the mathematical foundations of machine learning and optimization
• Proven experience building and deploying advanced AI systems, including Large Language Models (LLMs), multimodal, and generative AI architectures
• Exposure to agentic system design, retrieval-augmented generation (RAG) and prompt engineering techniques
• Strong 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 improvement
• Familiarity 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 dashboards

Requirements

• Proven experience in architecting and implementing end-to-end AI/ML solutions — from data ingestion and model training to deployment, monitoring and optimization
• Strong 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 integration
• Familiarity with handling complex data scenarios such as class imbalance, time-series forecasting and anomaly detection
• Understanding of security, data governance and compliance considerations in AI system design

Benefits

• Strong community: Work alongside top professionals in a friendly, open-door environment
• Growth focus: Take on large-scale projects with a global impact and expand your expertise
• Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications
• Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies
• Flexibility: Enjoy flexibility – full remote working possibilities
• Care: We've got you covered with company-paid premium medical package through Luxmed
• Benefits: Access the MyBenefit cafeteria platform, allowing you to choose perks that best suit your lifestyle and needs