Top Artificial Intelligence Jobs in Krakow

Build and maintain user-facing web apps and conversational interfaces for agentic AI logistics solutions. Focus on frontend performance and UX, integrate UIs with backend services and agent systems, contribute backend components, ensure quality through testing and iteration, and collaborate with cross-functional teams to deliver scalable human-AI interaction flows.

Lead architecture and delivery of an agentic AI framework: design and productionize agent components (planning, tool-use, memory, safety), provide SDKs/APIs and reference implementations, mentor engineers, drive cross-team alignment, and ensure reliable, scalable, customer-facing agent-based systems.

Build and maintain scalable backend services, APIs, workflow orchestration, and integrations (including HERE APIs) to support agentic AI logistics solutions. Ensure production reliability through testing, monitoring, and CI/CD while collaborating with product and domain experts to deliver AI-driven planning and optimization features.

Lead a cross-functional engineering team to build and evolve an Agentic AI framework integrating location intelligence and customer workflows. Own core framework delivery, ensure engineering quality, partner with product and platform teams, and embed AI-assisted workflows to boost productivity.

Lead design and implementation of automated testing and evaluation pipelines for agentic AI logistics systems. Build scenario simulations for routing, time windows, capacities and geospatial edge cases, validate integrations with HERE and external APIs, generate synthetic test data, incorporate statistical validation for non-deterministic LLM outputs, and integrate tests into CI/CD while collaborating with engineers and domain experts to find and mitigate failure modes.

Build and maintain data ingestion, transformation, semantic layers, and analytics pipelines to support dashboards, KPIs, and GenAI-driven insights. Ensure data quality, metadata enrichment, and integration with GenAI/RAG systems while collaborating with analysts and engineers to translate business needs into reliable analytical products.

Design and govern agentic interfaces and domain architectures for AI-driven workflows across logistics, fleet, and mobility. Translate customer workflows into reusable agent skills, context and memory models, and orchestrations. Drive data-centric learning loops with data science, define integration patterns with enterprise systems, and ensure security, observability, and explainability. Own concept-to-implementation delivery and continuous improvement of domain agent capabilities in production.

Assist customers with claims and queries via various channels, utilizing legal knowledge and following procedures in a shift-based environment.

Assist air passengers with their claims through timely communication across various channels. Provide legal advice with training support and follow operational procedures.

Assist customers with claims related to delayed or cancelled flights, providing support through various communication channels and utilizing legal knowledge to offer assistance.

Assist air passengers with claims by communicating through email, chat, and social media, and utilizing legal knowledge for guidance.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

The role involves managing risks related to AI systems, coordinating with various functions for compliance, and preparing assessments. Ideal candidates should have a background in IT governance and project management within regulated environments.

Lead engineering activities for productizing Deep Learning models, mentoring team members, collaborating across units, and optimizing DL workloads.

Serve as a strategic finance business partner to regional sales leaders, driving commercial rigor across bidding, contracting, forecasting, and profitability. Deliver financial planning, data-driven insights, risk management, compliance support, and cross-functional reporting while supporting systems and credit management.

Design, build, and deploy AI agents and conversational solutions using Microsoft Copilot Studio and Power Platform. Integrate LLM-based, RAG-enabled systems with enterprise APIs, implement monitoring/analytics, ensure security and governance, and collaborate with stakeholders in Agile delivery.

The role involves designing scalable data pipelines and architectures, integrating multiple data sources, and ensuring data quality and governance within the CMDB and Asset Intelligence platform.

The Data Science Lead will lead a team of data scientists in developing ML systems for logistics, overseeing the entire lifecycle from research to production.

The role involves designing and deploying AI systems for clinical operations, developing models for decision-making, and ensuring AI implementation aligns with data governance standards. Responsibilities include collaborating across teams, enhancing operational efficiency, and advancing AI applications in a regulated environment.

Manage a team of data scientists to build ML systems for logistics, overseeing the entire lifecycle, mentoring, and collaborating with technical teams.

Lead and co-own development of a scalable data platform for analytics and ML. Define roadmap, translate requirements into backlog, work with engineers on architectures, pipelines, storage, MLOps, data quality, and drive agile delivery while participating in technical decisions and stakeholder communication.

Lead the Business Unit's data, analytics and AI strategy, prioritize and translate AI opportunities into use cases, manage the AI portfolio and governance, ensure data quality and compliance, drive cross-functional delivery, budgeting, stakeholder alignment, change management and capability building.

The AI Adoption Manager will implement AI solutions, automate processes, and train teams to enhance efficiency and productivity across the organization.

Join our team to create and implement AI solutions, focusing on cloud applications and ETL processes while supporting entrepreneurs with the public cloud.

Design and implement robotics software and AI/ML models for embedded systems, focusing on performance optimization and system integration. Lead architectural decisions and ensure production readiness of robotics and edge AI solutions.