Top Artificial Intelligence Jobs in Poland

Design and maintain AI infrastructure (cloud/on‑prem/hybrid), build CI/CD and MLOps pipelines, manage containers with Docker/Kubernetes, implement IaC with Terraform, enable model operationalization, monitor and secure services, collaborate with data scientists and engineers, and troubleshoot production incidents.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Design, build, and maintain cloud-native AI platforms and infrastructure; develop, deploy, and optimize AI agents and agentic runtimes; enable teams with AI-assisted development and automation; collaborate with engineers and AI specialists to deliver scalable, secure, production-ready AI solutions.

Build and maintain ING's Data Analytics Platform on Google Cloud. Develop Golang infrastructure automation and platform tooling, implement IaC with Terraform and CI/CD, onboard and support platform tenants, improve monitoring/observability, and participate in operational stability and on-call support.

Design, implement and deploy production-grade AI agent systems and REST microservices on Azure. Implement function calling, tool orchestration, prompt engineering, multi-agent (A2A) orchestration, integrate agents with enterprise APIs and data sources, and collaborate on developer standards, code reviews and incident retrospectives.

Create high-volume, high-quality marketing content using generative AI and AI agents. Produce video, image, and social content, develop attention-driving campaigns, track AI and culture trends, and iterate quickly with the marketing and founding team.

Lead AI-native engineering: build and ship production-grade features, convert AI-assisted prototypes into reliable systems, own architecture/security/quality, direct AI coding agents, define engineering standards, and work closely with founders on product and technical strategy.

Build features, prototypes, and demos using modern AI coding tools and agents; iterate prototypes into reliable, scalable production; direct and evaluate AI coding agents; collaborate closely with founders and senior engineers; explore and improve AI development workflows to accelerate product delivery.

Conduct research applying advanced ML (GNNs, diffusion models, transformers) to semiconductor/chip design. Develop algorithms, prototype with modern ML frameworks, collaborate cross-functionally, publish in top conferences, and contribute to EDA tools.

Lead enterprise process knowledge capability to convert Agent Operating Procedures into structured, reusable, machine-executable knowledge within a Knowledge Graph. Define AOP standards, templates, taxonomies, and governance; run SME elicitation; partner with engineering, AI, and product teams to integrate process knowledge into agentic and automation systems; drive standardisation, quality, auditability, and measurable value across global delivery.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.

Design, build, and scale production AI agents and backend services for conversational reasoning, retrieval, tool-calling, and workflow automation. Integrate GDS/APIs, own architecture for distributed AI systems, improve model performance, observability, and evaluation, and define engineering best practices.

Lead a team of senior full-stack developers to design, build, and ship scalable full-stack features and admin tools using Next.js, React, TypeScript, Prisma, and PostgreSQL. Own end-to-end delivery, architecture, database design, API integrations (e.g., Stripe, Supabase), performance optimization, testing, deployment, and mentoring, leveraging AI-assisted development tools like Cursor IDE.

Lead and mentor a senior full-stack team to design, build, and ship scalable web applications using modern stacks and AI-assisted tooling. Architect systems, optimize database performance, integrate third-party APIs, own delivery from requirements to deployment, and establish engineering best practices.

Design, build, and maintain automated test suites, evaluation scenarios, metrics, and datasets for AI-powered features. Automate QA workflows with Python and CI/CD, test APIs and ML model outputs, define quality strategy and acceptance criteria, create CI/CD quality gates, mentor teams, participate in code reviews, and document findings.

Design, build, and maintain production AI workflows (agents, prompts, retrieval pipelines) integrating HR/Finance/Operations/CRM. Own orchestration, monitoring, evaluation, and continuous improvement to ensure reliable, auditable decision quality and measurable business outcomes.

Join the AI & Innovation team to build and maintain full‑stack Python services, integrate ML/LLM models into production, develop scalable APIs and data pipelines, optimise AWS infrastructure, and write unit/integration tests to ensure reliability for high‑traffic jobseeking products.

The AI Engineer will build and maintain AI agents for performance media trading, integrate data, ensure system reliability, and implement evaluation frameworks.

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.

Conduct discovery and audit sessions to analyze support workflows, KPIs, and platforms (Zendesk, Freshdesk, Intercom). Identify automation opportunities, design scalable AI-driven workflows (chatbots, NLP ticket classification, auto-triage, agent assist), create AI readiness roadmaps, prioritize by ROI, and deliver actionable recommendations to stakeholders.

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.