Top Artificial Intelligence Jobs in Krakow

The trainee will implement AI solutions in factory settings, deploy tools for industrial challenges, analyze data for machine learning models, and support local teams across European sites.

Define and govern enterprise-wide application architecture, set guardrails (modularity, buy vs build, SaaS vs custom), guide portfolio rationalization, assess current and future IT landscapes, oversee architectural reviews, and align application strategy with business capabilities across a decentralized organization.

Design, build, and deploy integrations and AI-enabled workflows for business efficiency. Own MCP Gateway, drive automation, and collaborate cross-functionally.

This role focuses on enhancing brand visibility in AI-generated answers through content optimization, community engagement, and outreach efforts. Output measurement is key, with targets for content delivery and community participation.

The AI/ML Data Engineer develops solutions for ETL processes, implements data quality metrics, and adapts technologies for big data processing while leveraging AI/ML data platforms.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Lead the development of our SaaS insurance platform, mentoring a team of engineers, integrating AI capabilities, and ensuring scalability and security while driving technical strategy and innovation.

The AI Solutions Architect will lead the design of GenAI solutions, evaluate AI frameworks, support presales efforts, and ensure solutions are scalable and secure.

The AI Content Expert II creates and annotates complex training data for LLMs, ensuring quality and producing text across various styles. Responsibilities include auditing work, making independent decisions, and collaborating with scientists and engineers for data quality improvement.

The AI Engineer will design, build, and deploy AI solutions, focusing on LLM applications and automation while collaborating closely with clients to provide impactful AI-driven solutions.

Define and operationalize ontology- and knowledge-graph-driven governance for Data & AI platforms. Design semantic layers, business glossaries, taxonomies, and metadata-driven governance. Collaborate with architects, engineers, InfoSec, compliance, and AI teams to embed Agentic and Responsible AI governance, lead client workshops, and shape enterprise-scale data governance solutions.

Design, develop, test, and deploy data solutions and AI-driven systems for a banking platform. Build and maintain Data Lakehouse pipelines, data models, ingestion (CDC/streaming), dashboards, and conversational LLM integrations while ensuring data quality, governance, and regulatory compliance.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Senior Software Engineer will design, develop, and support cloud software using C# and Azure, while mentoring team members and contributing to project architecture.

The AI Product Owner translates business needs into agent-ready requirements, manages the product backlog, and ensures product delivery across various lifecycle stages, collaborating with engineering and architecture teams.

The VP of Business Development will drive commercial growth in Europe, focusing on strategic opportunities with renewable energy stakeholders and building relationships to enhance market presence.

You will modernise legacy services using AI, implement automation in the development lifecycle, and demonstrate AI-first practices within a team of senior engineers.

Lead product vision and strategy for the Mosaic Data Intelligence portfolio. Manage P&L, roadmap, investments, and priorities. Capture customer and market needs, translate into user stories, work with engineering and commercial teams to deliver AI/data solutions, support sales and stakeholder engagement, triage maintenance, and conduct demos.

Lead product vision, roadmap, and P&L for Data, AI and Insights products in travel. Translate market and customer needs into backlog, write user stories, support sales and delivery, guide scrum teams, analyze maintenance issues, and drive product-market fit and profitability.

Design, build, and maintain scalable, secure cloud infrastructure across AWS and Azure using Terraform, Docker, and CI/CD. Manage production environments, monitoring, security, IAM, secrets management, automation, cost optimization, and collaborate with dev/DevOps teams to ensure high availability and reliability.

The role involves defining AI data architecture, managing data quality, and ensuring security while guiding teams on best practices for data governance and AI integration.

The role focuses on modernizing enterprise data architecture for AI readiness, involving data governance, quality, security, and orchestration using Airflow. Responsibilities include defining standards, establishing data contracts, ensuring data quality, and providing mentorship.

The AI Data Engineer will design and build AI data pipelines, ensuring reliability and quality for predictive intelligence in the Large Market Model.

The Strategic Commercial Operations Analyst develops AI-driven sales analytics solutions, enhances performance tracking, and delivers actionable insights using Power BI and machine learning techniques.

Senior Director analyst providing thought leadership and actionable research on infrastructure and operations AI strategy. Produce insights, presentations, and client advisories; guide AI infrastructure, cloud adoption, integration, governance, and vendor selection. Lead research agenda, mentor analysts, collaborate cross-functionally (infrastructure, engineering, enterprise architecture, cybersecurity), support sales, and represent Gartner at events. Drive process improvements and influence senior stakeholders to align infrastructure and operations with business outcomes.