Top Artificial Intelligence Jobs in Poland

Design, build, and deploy production-grade AI agents and agentic workflows by orchestrating LLMs, retrieval systems, and tools; integrate solutions into client applications, optimize agent performance, ensure observability and LLMOps best practices, and collaborate with engineering and data teams.

Design, build, test and support batch and streaming data pipelines and curated datasets on a modern lakehouse/AI platform. Improve data modelling, quality, reconciliation, performance and operational reliability, partner with stakeholders, and provide technical leadership for delivery.

Design, architect, and deploy end-to-end AI solutions (RAG pipelines, autonomous agents) to improve risk management. Translate regulatory and capital requirements into technical specifications and prompts, build infrastructure and testing strategies, and collaborate with regulators, senior risk managers, and engineering teams on distributed AI systems.

Design, build, test and support batch and streaming data pipelines and curated datasets on a Lakehouse/AI data platform. Implement data modelling, schema evolution, partitioning and data quality controls. Work with stakeholders to deliver production-ready, well-tested, high-performance data products and support operational monitoring and reconciliation.

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.

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.

As a Senior Embedded AI Engineer, you'll integrate Large Language Models into robotics, optimize AI models for embedded platforms, and work on simulations with real robots.

Post-sales, customer-facing role that drives developer adoption of AI tooling by designing and running hackathons, Customer Developer Days, and repeatable facilitation infrastructure. Partner with deployment and success teams to diagnose adoption stalls, run high-touch interventions, capture outcomes, and evangelize results. Must be technically credible with developers and able to troubleshoot and demonstrate AI coding tools in real time.

Design and implement full-stack applications and AI agents. Collaborate with teams to deliver customer-focused solutions while ensuring secure and reliable development practices.

Design and implement full-stack applications and AI agents while mentoring engineers and leading project ownership, focusing on rapid development and deployment of AI capabilities.

Translate legal expertise into AI-powered workflows by designing, configuring, and testing Libra Assistants. Partner with clients to map processes, run pilots, enable adoption, and provide product feedback to improve prompt quality and accuracy. Create learning materials and drive high customer satisfaction while working cross-functionally with Product, Engineering, Sales, and Customer Success.

The Commercial AI Solutions Analyst will collaborate with teams to implement AI initiatives and ensure data quality for business insights. Responsibilities include data validation, user acceptance testing, and promoting AI literacy within sales.

Chatdesk Experts provide support for e-commerce brands through social media and email, working remotely and setting their own schedules.

Design, build, and improve ML models and production pipelines; collaborate with engineers, data scientists, and PMs; develop experimentation roadmaps; set up reproducible environments; monitor and maintain production models; document models and processes; propose and apply new AI/ML solutions.

Evaluate AI coding agents end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide opinionated feedback, distinguish response quality levels, and help define standards for great AI-developer interactions. Participate in take-home evaluation and interview as part of a rolling, project-based engagement.

Identify, prioritize, prototype, and implement LLM- and AI-driven business use cases using no/low-code and automation tools. Measure impact on business metrics, enable independent AI use across functions, build an internal AI community, and monitor/integrate market AI solutions.

Design and introduce NVIDIA AI solutions for telecommunications (network management, cloud/edge/NFV), lead technical aspects of complex deployments and PoCs, create trainings and technical content, and drive customer adoption and integration of AI platforms.

Lead end-to-end process analysis, redesign, and transformation across finance and non-finance domains. Prioritize and deliver AI-enabled automation and BI solutions (Power Platform, Power BI, Copilot), manage delivery pipelines, coordinate cross-functional stakeholders, and drive change management, training, and adoption.

Monitor AI-enabled tools to manage supplier inquiries, resolve escalated AP exceptions, ensure service quality, reconcile accounts, maintain documentation, and drive continuous improvement in AI-supported Accounts Payable processes while collaborating with suppliers and internal stakeholders.

Manage month-end journal entries, intercompany and bank reconciliations, and balance sheet account reviews using AI-enabled tools and advanced Microsoft solutions. Ensure US GAAP/IFRS compliance, support regional group reporting, identify automation opportunities, and contribute to Record-to-Report transformation with RPA and AI-driven solutions.

Lead strategy and delivery of AI-driven knowledge management for global service operations. Define product roadmap, data architecture and governance, identify automation opportunities, steer cross-functional agile squads, manage product lifecycle and stakeholder alignment, and drive global rollout and adoption.

Build production-grade generative AI applications using private LLMs: design prompts, implement RAG/vector search, integrate LLMs into backend services and web UIs, ensure enterprise security/compliance, perform data analysis, and collaborate on end-to-end deployments and automation.

Lead multiple consulting projects end-to-end, oversee AI and tech implementations, coordinate cross-functional teams and C-level stakeholders, manage risks, resources, and deliver business value.

Post-sales technical lead for strategic EMEA accounts, advising on cloud-native and AI deployments. Own technical relationships, troubleshoot escalations, design architectures for LLM/agentic workloads, drive product adoption, deliver training, and feed customer insights to Product and Engineering.

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.