Top Artificial Intelligence Jobs in Poland

Develop, fine-tune, and deploy LLM-based AI solutions and automations. Integrate models with APIs, databases, CRMs and cloud platforms, implement RAG and prompt engineering, monitor production performance, and collaborate with product and engineering teams.

Remote SDR responsible for outbound prospecting, qualifying leads, booking demos, maintaining CRM records, collaborating with marketing and sales, and meeting monthly KPIs in the AI SaaS space.

Lead design and implementation of scalable automation systems and integrations using GoHighLevel and tools like n8n/Make/Zapier. Build workflows for lead generation, nurturing, content creation, and sales pipelines; integrate CRMs with email, calendars, payments, and project tools. Maintain documentation (SOPs), advise clients, provide technical support, and own internal automation infrastructure to ensure reliability, scalability, and clear communication with non-technical stakeholders.

Lead design, build, and scale client-facing and internal automation systems. Create advanced workflows (GoHighLevel, n8n/Make/Zapier), integrate platforms via APIs/webhooks, document SOPs, advise clients, maintain CRMs and troubleshoot live systems for reliability and scalability.

Lead development of scalable AI-powered GTM systems, migrating from no-code to Claude Code agent architectures. Build integrations, data pipelines, and reusable agent frameworks; ensure reliability, observability, and cost optimization. Hire, mentor, and manage a distributed engineering team while evaluating emerging AI tools and driving platform innovation.

Manage and deploy AI-driven automation and workflows, onboard clients, translate requirements into actionable automations, design prompts for LLMs, troubleshoot and iterate systems, coordinate with AI engineers, and track project timelines and performance.

Build, launch, and optimize high-performance outbound campaigns and automated GTM systems using Clay, Claude, SmartLead, HeyReach, n8n, and APIs. Translate buying signals into targeted prospecting workflows, iterate on messaging and sequences, track CRM attribution, and optimize for pipeline outcomes and campaign KPIs (launch velocity, conversion, pipeline contribution).

Design, develop, and deploy AI/ML models and LLM-powered workflows (chatbots, copilots, automation). Integrate models with APIs and SaaS platforms, fine-tune prompts, work with structured/unstructured data, monitor performance, and collaborate with product and engineering teams to deliver scalable AI solutions.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

Design and build workflows using node-based AI systems for video and image generation. Collaborate with teams to enhance AI-driven processes and create demos for various stakeholders.

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.

Develop and maintain LLM-powered applications using Python, focusing on coding optimizations, CI/CD pipelines, and cloud infrastructure on GCP.

Build and own end-to-end product features across backend and frontend. Implement Python services with SQLAlchemy/GraphQL/PostgreSQL, integrate external systems (GDS, payments, email/SMS), and use AI agents daily to plan, verify, and ship high-quality features.

Lead enterprise growth across top European law firms and corporate legal departments, manage retention and expansion through a team of Retention Managers, oversee digital revenue and e-commerce channels, coach cross-border account executives, negotiate high-value enterprise agreements, and present commercial strategy to executive leadership.

Design, build, and maintain agentic workflows and reusable automations for product teams. Integrate automations with business systems via APIs, test and iterate solutions, and train stakeholders to use and maintain tools.

Build and maintain a Google Cloud data analytics platform: design architectures, implement cloud-ready IaC solutions (Terraform), automate deployments (Docker, Kubernetes, CI/CD), manage monitoring/alerting, support tenants and provide on-call assistance while collaborating on design and experiments.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Lead product vision and roadmap for an AI shopping assistant, prioritize ML use cases, design validation experiments, own evaluation metrics and feedback loops, define consumer go-to-market, and drive cross-functional delivery with engineering and business teams.

Design, build, and deploy AI-powered automations and analytics using enterprise data. Develop anomaly detection, forecasting, predictive models, and integrate AI solutions with UiPath workflows. Produce dashboards, decision-support tools, and scale proofs-of-concept into production while collaborating closely with business stakeholders across Finance, Procurement, Supply Chain, and Shared Services.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.