Top Artificial Intelligence Jobs in Krakow

Lead privacy engineering strategy and automation across the product lifecycle. Own Privacy by Design, DPIAs, privacy assessments, DSR processes, privacy controls, monitoring, metrics, and governance. Build scalable tooling and technical standards across cloud architectures, APIs, data platforms, and products. Advise Product, Engineering, Security, Architecture, Legal, and Privacy teams while applying privacy-enhancing technologies, AI governance, and regulatory frameworks.

Leads analytical methodology and evaluation for AI-based healthcare and pharmaceutical workflows. Owns model selection, cohort and HCP segmentation, agent decision logic, and evaluation frameworks. Partners with engineering, data architecture, and governance teams to productionize rigorous analytical methods, identify new data and techniques, communicate insights, and mentor data science and engineering colleagues.

Leads data science methodology and advanced analytics for AI-enabled Medical Affairs workflows. Develops and evaluates statistical, machine-learning, NLP, and AI models using healthcare and real-world data; defines validation, monitoring, and decision frameworks; partners with engineering, governance, and business teams to operationalize solutions. Provides technical leadership, mentorship, documentation standards, and strategic guidance while ensuring privacy, compliance, responsible AI use, and clear communication of analytical findings.

Senior Commercial Counsel will negotiate enterprise sales, partnership, vendor, services, data licensing, and marketing agreements. The role advises on privacy, intellectual property, data security, AI law, and cross-border data transfers across the UK/EU and APAC. Responsibilities include building scalable legal processes, supporting sales and business development, managing international regulatory issues, and translating evolving AI legal developments into practical guidance for a fast-growing company.

Own the technical direction for validating AI agent-generated software. Build prototypes and platform systems that identify gaps between passing tests and working features, provide mid-loop feedback for agent self-correction, and support trusted development across Rust, Ruby, and Go. Collaborate with engineering teams to drive adoption, measure trust and validation quality, establish architecture, review designs, and mentor teammates in a remote asynchronous environment.

Design and build scalable platform capabilities that expose location intelligence to agentic AI. Implement reliable LLM-driven decision pipelines, optimize latency/cost for edge deployments, define evaluation and reliability strategies, and lead cross-functional technical direction and integration.

Design, build, deploy, and evaluate production-grade generative AI applications using foundation models and LLMs. Develop RAG systems, AI agents, fine-tuned models, evaluation pipelines, and high-quality datasets for financial workflows. Optimize latency and cost while implementing scalable deployment, monitoring, safety guardrails, and responsible AI practices. Collaborate cross-functionally to deliver AI-powered solutions for finance and accounting teams.

Manage strategic client relationships across multiple industries, serving as the primary contact and ensuring satisfaction, commercial performance, and solution alignment. Translate client goals into actionable plans, lead cross-functional initiatives, support renewals and cross-sell opportunities, monitor performance metrics, resolve issues, and represent customer needs internally. Frequent travel to Genoa, Italy is required for client meetings and on-site engagements.

Develop and maintain CI/CD workflows, engineering tools, and automation for the Packet Core area. Investigate and troubleshoot issues, improve CI/CD environments, and build internal applications using Python, Bash, Kubernetes, Docker, GitLab CI/CD, Jenkins, and Elastic Stack. Develop AI agent tools based on Model Context Protocol. The role requires strong Linux, DevOps, software development, integration, and testing knowledge in a hybrid Krakow environment.

Lead design and implement agentic AI systems: integrate services and models, optimize and fine-tune LLMs (LoRA/QLoRA), build datasets and evaluations, run experiments to improve reliability, cost, and latency for production workflows.

Manage relationships with AI-native startups, scaleups, and research labs; understand their technical and business needs; develop high-value NVIDIA solutions; drive adoption of AI platforms; coordinate with solution architects, engineering, business development, and go-to-market teams; cultivate ecosystem partnerships, customer references, case studies, and emerging use cases; and represent NVIDIA at industry events.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Create experiential graphic design for global events, trade show booths, environmental graphics, pop-ups, and summits. Translate creative direction into spatial designs that work across materials, architecture, lighting, and physical environments. Develop brand design languages, contribute to ideation, present concepts, prepare production-ready artwork, and coordinate junior designers or external partners. The role also supports broader brand graphic design initiatives and requires independent project ownership across international teams.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

Participate in Veeva’s Consultant Development Program, configuring cloud software, testing features, solving customer problems, managing deliverables, and advising Life Sciences customers. Associates receive intensive onboarding, work directly with customers within three months, and can advance to Consultant in under two years. The role is remote in Poland but requires residence within 60 minutes of Krakow, Warsaw, or Wroclaw and travel up to 20–30% of the time.

Supports strategic governance and business operations across client experience, operational excellence, risk and resiliency, and employee engagement. Produces metrics, reports, presentations, and analysis; tracks initiatives, risks, issues, and escalations; supports strategic and transformational projects; and uses technology and AI tools to improve processes. The role requires strong organization, communication, analytical, presentation, collaboration, and prioritization skills in a hybrid environment.

Design and deliver scalable Generative AI architectures using LLMs, RAG, agents, automation, and cloud platforms. Translate client business needs into technical solutions, lead discovery workshops and pre-sales activities, create architecture proposals, and guide engineering teams through implementation. The role also covers AI governance, responsible AI, system integration, monitoring, lifecycle management, and stakeholder communication.

Develop backend features in .NET, maintain APIs, support integrations, write unit-tested code, analyze bugs and logs, and participate in reviews and technical workshops. The role involves using AI tools responsibly for coding, debugging, research, refactoring, and automation while verifying generated solutions. Candidates collaborate with experienced engineers and contribute to document management software supporting clinical research.

Support banking AI transformation by managing parallel use-case analysis workstreams, facilitating stakeholder workshops, gathering evidence, documenting processes and requirements, and scoring opportunities. Produce decision-ready dossiers covering business value, feasibility, risk, controls, regulatory obligations, and implementation complexity. Assess responsible AI requirements including the EU AI Act, privacy, cybersecurity, explainability, auditability, human oversight, and reproducibility while maintaining evidence quality and human review.