Top Artificial Intelligence Jobs in Poland

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

Lead design and implementation of LLM-based features and agentic workflows for an enterprise SaaS OMS platform. Build and optimize models, data pipelines, and AI infrastructure; deploy, monitor, and fine-tune production models; implement responsible AI guardrails; collaborate with product, data, and engineering teams; mentor junior staff and drive scalable, reliable AI solutions.

Design and develop software solutions for AI/ML applications, propose new approaches to optimization problems, and collaborate with global teams in research and development.

Build and ship secure, production-ready CI/CD and AI-integrated features end-to-end. Design, implement, and iterate on products (e.g., hardened GitHub Actions, agent features), work closely with Product and front-end teams, make architectural decisions, and extend Chainguard's agentic AI capabilities into customer-facing experiences.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.

Design and deliver AI agent ecosystems, collaborate with teams on business goals, and provide mentorship while staying current with AI advancements.

This role involves designing, developing, and deploying AI and automation solutions, ensuring integration with enterprise systems, and meeting security standards. The position requires hands-on engineering skills in AI development, particularly with Python and AI frameworks.

Execute structured prompt testing, prototype lightweight AI workflows, configure and validate custom GPTs, document prompt libraries and exemplars, provide coaching and office-hour support, track usage patterns, and contribute technical input to enable responsible AI adoption across the firm.

The Process Efficiency Manager will lead continuous improvement initiatives, utilizing Lean Six Sigma methodologies, data analysis, and stakeholder management to drive operational excellence.

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.

Own lifecycle marketing campaigns across email, push and in-app channels: write copy, build automated customer journeys and behavioral triggers, run A/B tests, analyze performance with product analytics, and work with Product and Tech to optimize activation, retention and monetization.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Lead hands-on applied AI work: prototype demos, accelerate customer POC-to-production, perform technical onboarding, optimize distributed training and inference on GPU infrastructure, research and implement emerging ML techniques, and feed actionable product feedback while producing reusable assets and benchmarks.

Implement and maintain CI/CD pipelines, ephemeral AWS build environments, automated security scanning, and release promotion from Bitbucket to Artifactory. Manage CI/CD infrastructure via IaC, collaborate with global scrum teams, document as code, and automate repetitive ops tasks using AI agents.

Lead and deliver high-priority regional strategic initiatives across Europe by translating priorities into plans, governance, and delivery roadmaps. Coordinate executive governance, improve operational processes, embed AI-enabled productivity tools, drive stakeholder communication and change management, and strengthen the Business Impact team to ensure measurable outcomes and consistent execution.

Lead product direction and execution for major areas of an AI-enabled neobank app. Define roadmaps, priorities, standards, and success metrics across multiple squads; mentor PMs and guide designers and engineers; translate regulatory and operational constraints into product decisions; drive launch quality, post-launch learning and continuous improvement while focusing on user value and measurable outcomes.

Own product areas in BJAK's AI Neobank app (insurance, payments, savings, investing, travel). Define user problems, roadmaps, success metrics, and launch plans. Work cross-functionally with engineering, design, data, operations, compliance and business teams. Use data, research and feedback to iterate, simplify complex financial journeys, monitor performance, and balance UX, speed, business impact and compliance.

Lead the company’s ML/AI platform from experimentation through production, including SageMaker training infrastructure, model serving, inference pipelines, MLOps, and Java microservice integrations. Set AI/ML technical direction, develop GenAI and LLM retrieval and agent architectures, establish evaluation and safety guardrails, and partner with data science, DevOps, product, and engineering leadership on scalable ML roadmaps.

Lead development and evaluation of speech language models and automated scoring systems for learner and hiring applications. Build, fine-tune, and monitor acoustic, ASR, speech-to-speech, and LLM-based models; design experiments and validity analyses; perform error analysis and rater reliability studies; integrate with product and UX; apply responsible AI practices and support production monitoring and governance for high-stakes assessments.

Lead R&D and implementation of ML and statistical learning capabilities for English language learning products. Design, build, and monitor production-ready models (NLP, speech, psychometrics), document and present results, mentor junior colleagues, collaborate with engineering, and publish research.

The Sales Operations & AI Manager will oversee CRM systems and automations, optimize sales processes, and build AI workflows to enhance lead generation and data management.

The Senior Python Engineer will design, develop, and maintain internal AI-driven tools, APIs, and workflows, focusing on automation and system integrations to enhance efficiency at Capital.com.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.