Top Artificial Intelligence Jobs in Krakow

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

Lead architecture and hands-on development of an AI-native underwriting platform. Design scalable backend services in Python, integrate with React/TypeScript frontends, promote engineering standards, implement observability and security, and use AI-assisted development tools to improve productivity while mentoring the team and driving the platform from MVP to production.

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.

Join the MLOps team to deploy, maintain, monitor, and optimize machine learning models in production. Build data and model pipelines, implement CI/CD for ML, ensure model performance and cost efficiency, and collaborate cross-functionally to deliver scalable AI solutions.

Lead design, build and deploy advanced AI systems and LLM-driven applications (RAG, agents). Architect scalable ML/LLM pipelines, apply MLOps/LLMOps, integrate with enterprise systems, ensure security and compliance, mentor teams, and act as technical SME in presales and delivery.

Design polished mobile-first and web interfaces for BJAK's AI and financial products. Turn requirements into wireframes, flows, prototypes and high-fidelity UI; maintain the design system; collaborate with PMs and engineers for pixel-perfect implementation; iterate from user feedback and analytics while ensuring accessibility, responsiveness and consistency across platforms.

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

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.

Develop AI-enabled workflows and methods to accelerate design, simulation, control, and validation of complex power-electronics systems. Apply ML (surrogate models, optimization, RL, Bayesian methods) integrated with MATLAB/Simulink, PSCAD, or PLECS to enable design-space exploration, model reduction, anomaly detection, and reliability assessment. Collaborate with local and global teams, external partners, and disseminate results via reports, patents, and publications.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

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.

Build end-to-end Generative AI solutions (chatbots, voicebots, Talk-to-Data) including data ingestion, retrieval/RAG pipelines, orchestration, model selection/fine-tuning, MCP integrations, evaluation, deployment, and support pre-sales and delivery activities.

Lead AI DevOps Engineer to architect, deploy, and automate scalable, secure AI/ML/GenAI solutions. Responsibilities include model serving, CI/CD, IaC, cloud (Azure) infrastructure, Kubernetes, monitoring, cost optimization, stakeholder advising, mentoring engineers, and coordinating cross-functional teams to deliver production-ready GenAI applications.

Build end-to-end AI-native product features across frontend, backend, and model integrations. Design and deploy agent workflows, streaming real-time interactions, reliability and fallback mechanisms, and integrate LLMs, memory, and external tools to complete multi-step tasks. Collaborate with ML, backend, and product teams and iterate based on real usage and failure modes.

Build and ship end-to-end AI features: design prompts, tools, memory and agent workflows; convert model outputs into reliable behavior; debug model-to-product stack; optimize latency, cost, and reliability; create lightweight evaluation frameworks and collaborate with product and engineering to deliver production ML systems.

The Senior Software Engineer will design and implement AI capabilities, architecture, and product experiences, focusing on production AI features and collaborating with cross-functional teams.

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.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Build ShipMonk's AI domain: consult with stakeholders to identify real problems, design and implement AI/ML projects from prototype to production, make AI tools accessible to non-technical teams, and balance technical complexity with business impact.

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.

Lead and execute AI-first integrated marketing strategies and campaigns to drive acquisition, retention, product launches, community growth, and conversion optimization. Use AI across research, copy, personalization, automation, analytics, and reporting. Collaborate cross-functionally to build funnels, scale education and partnerships, run webinars and evergreen campaigns, and continuously experiment to improve ROI and customer journeys.

Lead design and scaling of AI-first operational systems across the company. Improve processes, documentation, reporting, automation, and cross-functional execution while partnering with executive leadership to increase efficiency, KPI visibility, and AI adoption.

Design, build, test, document, deploy, and improve AI-first business automations across CRM, HR, Sales, Marketing, Customer Success, and Operations using no-code/low-code platforms, APIs, webhooks, and AI agents to increase efficiency, accuracy, scalability, and user experience.

Partner with executives to identify, prioritize, and implement AI opportunities across the organization. Develop AI roadmaps, evaluate technologies and vendors, redesign workflows, increase automation maturity, measure outcomes, establish AI governance, and drive business transformation to improve customer experience, productivity, and decision-making.

Lead visual design across product, marketing, education, and business assets using strategic systems thinking and AI-assisted tools. Create brand identity, presentations, reports, landing pages, social assets, and production-ready collateral while ensuring consistency, quality, accessibility, and cross-functional collaboration to improve user understanding and engagement.