Top Artificial Intelligence Jobs in Krakow

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

Design, develop, and productionize AI/ML solutions within the Workday practice. Integrate models into production, implement MLOps (CI/CD, versioning, monitoring), use cloud AI services and container orchestration, build data pipelines, and collaborate with cross-functional teams to ensure scalable, reliable AI-driven features.

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.

The AI Application Engineer will develop AI-enabled web applications, internal tools, and workflows, focusing on quick delivery while ensuring software quality.

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.

Design, build and ship native iOS features for BJAK's AI Neobank app using Swift. Implement insurance, payments and financial flows; integrate REST APIs; optimize performance, crashes, memory and battery; use analytics and production feedback; collaborate with product and design to create clean mobile user journeys and AI-assisted experiences where helpful.

Build and ship native Android features in Kotlin for an AI-enabled neobank. Collaborate with product and design to create clean user journeys, integrate backend APIs, improve performance and reliability, use analytics and production data to iterate, and implement on-device AI where it improves the UX.

Build and ship native Android features for an AI-enabled neobank using Kotlin. Design clean mobile flows for payments, insurance, claims and financial services, integrate backend APIs, improve performance and reliability, use analytics to iterate, and implement on-device AI where it improves the user experience.

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.

As an AI-First Frontend Engineer, you will develop high-performance, AI-integrated user interfaces for telehealth applications, manage team workflows, and optimize web performance.

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.

Lead AI adoption for business teams: run assessments, prioritize use cases, design and deliver workshops, activate champions, remove blockers, track adoption KPIs, and hand teams off as self-sufficient while routing engineering needs to technical teams.

Design, develop, and maintain automated test suites for web apps, APIs, and AI/LLM features. Evaluate LLM outputs for accuracy, relevance, and hallucinations; create prompt tests using Promptfoo; build Playwright-based UI automation; write reusable Python scripts and Postman collections; integrate tests with CI/CD; collaborate with product and engineering in Agile ceremonies.

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.

Build and maintain enterprise-grade software tools within an Agile team, mentor peers, apply engineering best practices, use AI-driven development assistants, and collaborate across Product, Cloud, and Support to deliver high-quality solutions.

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.