Top Artificial Intelligence Jobs in Krakow

Design, build, and productionize AI/ML solutions within the Workday practice. Collaborate with data scientists and engineers to deploy scalable models, implement MLOps (CI/CD, versioning, monitoring), integrate with enterprise data systems and cloud platforms, and ensure reliability and performance of AI-driven features.

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.

Lead backend engineering and AI-agent integration efforts: design agent-ready systems, context pipelines, CI/CD and test guardrails, migrate monoliths to microservices, set API and schema standards, mentor engineers, and drive AI-assisted development practices.

Build production-grade internal AI platforms and tooling to accelerate engineering workflows: durable agentic workflows, change-intelligence, orchestration, observability, and integrations with CI/CD, source control, security scans, and service dependency systems to improve developer velocity, reliability, and operational confidence.

Design, build, and operate backend services for an AI-driven financial assistant. Own full SDLC, ensure performance, scale, resilience, and collaborate in small autonomous teams.

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.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

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 SEO and AI search initiatives end-to-end: improve technical SEO (site structure, crawlability, indexation, Core Web Vitals, structured data), increase visibility across search and LLM-driven surfaces, run experiments and reporting, build AI-powered workflows for content and automation, collaborate with product/content/analytics, and create data-driven content to drive measurable organic growth.

Design, build, and maintain end-to-end AI/ML solutions including data pipelines, model development, edge deployments, and integrations. Define camera and imaging setups for computer vision use cases, coordinate installations, monitor model performance, and collaborate with IT, software, and infrastructure teams to ensure scalable, secure, and maintainable solutions.

Design and build Python-based intelligent agents and multi-agent workflows using Autogen or similar frameworks. Integrate LLMs, develop cloud-native services, create async APIs, implement data ingestion and storage (SQL/NoSQL/vector DBs), ensure scalability, and contribute to orchestration, testing, documentation, and CI/CD.

Lead and deliver enterprise-grade Apple platform software: design features, break down customer problems, implement end-to-end solutions, mentor teammates, apply engineering best practices, ensure quality and reliability, and collaborate across product, cloud, and support in an agile environment.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Oversee product strategy and development in EdTech and AI, manage teams, and drive data-informed decisions aligned with business goals.

Develop and maintain automation testing frameworks, execute tests, and implement AI-driven quality practices while collaborating with product teams.

As a Staff Software Engineer at Redpanda, you will design and develop the Agentic Data Plane, lead technical projects, and enhance operational excellence in cloud services, focusing on reliability and scalability.

Design and build services for Redpanda's Agentic Data Plane, collaborating globally and ensuring high reliability and scalability of AI systems.

Conduct discovery and audits of client support operations, analyze workflows and ticket data, evaluate support platforms, design AI-driven automation strategies (chatbots, NLP, auto-triage, agent assist), create AI readiness roadmaps, and deliver actionable, executive-ready recommendations.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

Lead end-to-end development and integration of AI features (LLMs/ML) into web/mobile apps and APIs. Design AI-first UX, craft and optimize system prompts, build agentic workflows (LangChain/CrewAI/AutoGen), implement error-handling and hybrid cloud/on-prem deployments, and collaborate within product squads using Agile/Scrum.

Design and implement CI/CD and IaC for LLMs, automate model and dataset versioning, provision GPU/TPU infrastructure, enable safe experiment gates and progressive delivery, and build monitoring/observability and feedback loops for production LLM endpoints.

Lead design, build, and operate a multi-tenant AI platform and LLMOps infrastructure across cloud and on-prem. Own vector DBs, feature stores, model hosting (Kubernetes + GPU orchestration), and developer self-service tooling. Standardize LLM-as-a-service offerings and enable squads with APIs, templates, and documentation.

Produce high-performing AI-driven paid ads from concept to final cut using AI avatars, voiceovers, b-roll, and motion graphics. Match and iterate on existing ad styles, collaborate with copywriters, optimize for hooks/pacing/CTAs, scale volume, and stay current with AI tools to innovate creative formats.

Define product vision and strategy via market research and data analysis; build prioritized roadmaps; collaborate with PMs, designers, and engineers to launch products; communicate with stakeholders; track performance and iterate post-launch.

Perform quality checks on filters and options in desktop and mobile views, ensuring relevance to customer queries and preferences. Follow guidelines, conduct online research, review assessments for accuracy, and complete required training and qualification tests before starting.