Top Artificial Intelligence Jobs in Krakow

Design, build, test, deploy, and optimize advanced GoHighLevel CRM systems, funnels, websites, automations, and AI-powered customer journeys. Collaborate cross-functionally to improve lead routing, sales pipelines, campaign delivery, reporting, and documentation while continuously using AI to enhance workflows, QA, troubleshooting, and system scalability.

Own the full sales lifecycle for AI-powered products: prospecting, discovery, proposals, negotiation, closing, onboarding, and account growth. Maintain CRM, track pipeline and forecasts, collaborate with marketing/product/operations, and use AI tools to improve productivity and customer outcomes.

Coordinate end-to-end digital and live events, manage registrations and speakers, support email and social campaigns, improve attendee experience and community engagement, and leverage AI to optimize planning, content, reporting, and workflows across cross-functional teams.

Lead the execution of AI solutions for Galderma's AI Factory, overseeing architecture, engineering standards, and lifecycle management of AI products. Manage teams and collaborate with stakeholders to ensure security, operational excellence, and compliance.

The IT Business Analyst will translate AI aspirations into actionable use cases, manage stakeholder demands, and ensure regulatory compliance throughout project lifecycles.

Lead full-cycle recruitment for AI/ML roles across Europe and LATAM: build pipelines, partner with hiring managers, screen candidates, manage interviews and offers, and improve AI-focused hiring processes.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Design and lead end-to-end AWS architectures for enterprise AI/GenAI projects, run discovery and Well-Architected reviews, define IaC standards, advise on data and security architecture, support presales, and mentor engineering teams to deliver production-grade AI solutions.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Lead architecture and delivery for Fortives HR technology ecosystem, owning Oracle HCM, Boomi integrations, ServiceNow HRSD, Eightfold and LMS platforms. Define API-first integration patterns, implement AI/automation use cases, ensure data governance and compliance, and guide integration engineers while partnering with HR and IT stakeholders to modernize HR systems.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior ML Engineer will create and improve ML models, collaborate with teams, monitor models in production, and maintain documentation.

Design, build, and maintain ELT pipelines and dbt SQL models for analytics; optimize performance, scalability, and costs; apply AI-enabled tools to improve engineering workflows; collaborate to translate requirements into production-grade data assets.

Design and scale GTM systems and AI-powered workflows across sales, marketing, and product. Build agents, integrate Salesforce/HubSpot, turn product and user data into growth signals, create lead-scoring/routing/onboarding flows, identify bottlenecks, run experiments with founders to drive measurable revenue impact.

Own and evolve ShiftKey's AI infrastructure: organizational knowledge platform, retrieval and indexing (semantic RAG + re-ranking + HyDE), agentic cloud infrastructure on AWS, graph-based retrieval design, platform APIs, reference agent implementations, and AI cost/governance and observability for production-scale regulated (HIPAA) workflows.

Lead AI adoption and enablement for engineering teams via workshops, training, demos, and pair-programming. Design and implement AI-augmented SDLC workflows, evaluate AI tools and agents, create playbooks and best practices, and advise engineering leaders combining strategic consulting with hands-on technical delivery.

Design, build, and deploy AI agents and automations for Infrastructure & Operations using Microsoft Copilot Studio, Power Automate, Azure AI and scripting. Identify automation opportunities across I&O pillars, develop self-healing operations, create reusable AI patterns and enable engineers through training. Measure automation impact and ensure compliance with AI governance, security, and regulated-industry requirements.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

Build and deploy AI-native systems for BJAK's neobank: AI agents, RAG/retrieval systems, tool-calling and automations for onboarding, KYC, support, risk, CRM and operations; work with product and engineering to ship reliable, evaluated, low-latency, cost- and compliance-aware AI-enabled workflows.

Lead technical design and delivery of Data & AI systems: architect data pipelines, RAG and agent integrations, build FastAPI backend services in event-driven environments, use AI-assisted coding, mentor engineers, own production reliability, and coordinate cross-functional delivery from design through rollout and post-release operations.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.