Top Artificial Intelligence Jobs in Poland

As a Technical Product Manager, you will shape product vision for AI capabilities, collaborate with engineering and design teams, manage product lifecycle, and drive prioritization to deliver scalable solutions while communicating across technical and non-technical audiences.

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

Define and operationalize ontology- and knowledge-graph-driven governance for Data & AI platforms. Design semantic layers, business glossaries, taxonomies, and metadata-driven governance. Collaborate with architects, engineers, InfoSec, compliance, and AI teams to embed Agentic and Responsible AI governance, lead client workshops, and shape enterprise-scale data governance solutions.

As CEO/Co-founder, you will lead the creation of a new AI-driven B2B automation startup, defining product direction, validating market opportunities, driving growth, and managing operations.

The AI Engineer will design, build, and deploy AI solutions, focusing on LLM applications and automation while collaborating closely with clients to provide impactful AI-driven solutions.

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.

Lead and govern the Investor Operations AI portfolio: prioritize and deliver AI use cases, provide solution oversight (model selection, deployment), enable reuse and platform adoption, and ensure regulatory MRM compliance while partnering with engineering and data science teams.

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.

Partner with clients to identify Generative and Agentic AI opportunities, design scalable AI solutions and operating models, produce roadmaps and executive deliverables, support technical delivery and change management, and help embed AI capabilities and adoption across organisations.

Join Oliver Wyman's AI Capability & Adoption team to write and refine prompts, design AI-supported workflows, validate outputs, create prompt libraries and documentation, and provide coaching and office-hour support to scale responsible AI use across the firm.

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.

Lead AI-native backend development: design agentic workflows and context pipelines, write agent-actionable specs, build scalable cloud services (AWS), maintain CI/CD, databases, GraphQL/REST APIs, mentor engineers, manage incidents, and drive delivery of complex initiatives using AI as an accelerator.

Generate interactive, clickable prototypes quickly using AI design tools; iterate asynchronously and in workshops; collaborate with strategists and UI designers to hand off 70–80% complete prototypes with real interactions, copy, and edge cases; evangelize AI-first design workflows.

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.

Lead end-to-end presales for data, analytics, and AI opportunities: qualify deals, run discovery workshops, shape solution narratives and architectures, produce proposals/RFP responses, and build ROI/TCO value cases, coordinating Sales, Solution Architects, and SMEs.

Define and execute an AI adoption roadmap for software development: identify high-value AI use cases, select tools, run pilots, measure outcomes, scale initiatives, set governance and best practices, and educate development teams to integrate AI into the SDLC.

Designs and implements user-focused, secure software; creates technical and user documentation; debugs and supports production systems; leads feature delivery, code reviews, threat modeling, and mentors engineers while improving SDLC and agile practices.

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.

Lead end-to-end business operations workstreams for RDT Data & AI, translating requirements into implementation plans, performing deep-dive analyses, and improving processes (compliance, quality, dashboards, vendor management). Act as a trusted advisor to cross-functional stakeholders to drive operational excellence and organizational effectiveness.

Lead medium-to-large Data & AI initiatives, plan and execute Global Data Strategy workpackages, manage cross-stream dependencies, resources, and backlogs. Drive PMO governance, delivery of technical releases, and coordinate Metadata Management, MDM, and PBAC workstreams while partnering with data governance and mentoring engineering teams.

Drive enterprise adoption of agentic AI by identifying high-impact automation opportunities, prototyping agent-based solutions, partnering with process owners to re-engineer workflows, scaling prototypes into production, and measuring productivity and value creation while building reusable patterns and enabling an AI-native culture.

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.