Top Artificial Intelligence Jobs in Poland

The Technical Product Manager will define and drive AI-related product strategies, collaborating with cross-functional teams to enhance developer workflows. Responsibilities include roadmap execution, understanding user needs, and ensuring successful product launches.

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

Own the AI platform roadmap and build reusable capabilities (prompting, RAG, tool calling, agents, evaluation, observability). Run discovery, prioritize AI investments, partner with Product, Engineering, Design and Data, guide other PMs, define success metrics, and ensure scalable, reliable AI-powered features that deliver customer and business value.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

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.

Lead sales enablement activities for assigned product lines, support forecasting, financial modeling, and marketing program tracking. Provide analysis, training, and sales resources; act as liaison between field teams, product, and marketing; support proposals and global specialty sales where needed to drive commercial success.

Execute sprint-level product delivery for agentic AI products: own and prioritize the backlog, write sprint-ready user stories and acceptance criteria, run Agile ceremonies, partner daily with engineering, validate features via UAT and customer feedback, and communicate progress to stakeholders to ensure timely, high-quality releases.

As an AI Solution Architect, you'll lead AI strategies, design architectures, evaluate frameworks, ensure compliance, and collaborate with teams for production deployment in enterprises.

You will modernise legacy services using AI, implement automation in the development lifecycle, and demonstrate AI-first practices within a team of senior engineers.

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.

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

Identify and validate high-value AI use cases for financial services, lead discovery workshops, build ROI-driven business cases, map and redesign workflows, define technical requirements and acceptance criteria, prototype solutions with no-code tools, implement AI governance and ontologies, and ensure business-aligned delivery and compliance.

Manage end-to-end release lifecycle for a multi-agent AI platform: own release calendar, plan and orchestrate feature/patch/hotfix deployments, coordinate cross-functional teams, enforce quality gates and compliance, monitor release performance, run post-release reviews, mitigate risks, and lead release communications and escalations.

Lead development and operationalisation of Responsible AI frameworks and compliance processes. Translate regulations (EU AI Act, GDPR) into controls, implement risk assessment, bias detection, model validation, embed governance in development lifecycles, manage audits and incident response, and drive stakeholder engagement and training.

Support Shopify administration and Flow automations, maintain Google Apps Scripts and API integrations, manage access and SaaS subscriptions, configure Recharge subscription flows, and document processes. Use AI tools (Claude, ChatGPT) and n8n to build automations, test end-to-end, and liaise with vendors and internal teams to keep e-commerce systems running smoothly.

Founding AI Engineer responsible for end-to-end R&D and deployment of AI systems (LLMs, diffusion, vision), building rapid prototypes, orchestrating multi-model agentic workflows, integrating diverse APIs, and shipping scalable web applications to support e-commerce and future SaaS products.

Lead product vision and strategy for the Mosaic Data Intelligence portfolio. Manage P&L, roadmap, investments, and priorities. Capture customer and market needs, translate into user stories, work with engineering and commercial teams to deliver AI/data solutions, support sales and stakeholder engagement, triage maintenance, and conduct demos.

Lead product vision, roadmap, and P&L for Data, AI and Insights products in travel. Translate market and customer needs into backlog, write user stories, support sales and delivery, guide scrum teams, analyze maintenance issues, and drive product-market fit and profitability.

Design, build, and operate core AI systems (support, marketing, client orchestration) using LLMs and vector databases. Implement async pipelines, background jobs, and scalable production deployments. Measure performance, iterate, and improve system reliability, logging, and monitoring.

Build and own AI/LLM-assisted features in Ruby on Rails: integrate LLM APIs, implement retrieval/context patterns and prompts, ensure reliability, tests, fallbacks, performance, security, and production operability.

Build and own AI/LLM-assisted features in a Ruby on Rails production environment. Integrate LLM APIs, design prompts and retrieval/context patterns, implement safeguards and fallbacks, improve reliability, latency, cost, and security, and write/maintain unit, integration, and E2E tests. Debug production issues and iteratively improve system behavior.

The Pre-Sales Engineer will provide technical expertise in AI and data platforms, support clients during pre-sales engagements, and help design AI solutions aligning with business goals.

Lead end-to-end delivery of AI, ML, Big Data, and software projects for international enterprise clients. Act as primary client contact, define scope, manage risks, budgets, and resources, mentor cross-functional teams, drive business-aligned technical roadmaps, support pre-sales, and contribute to account growth and recruitment.

Develop and deploy AI features for a SaaS product, architect scalable backends, optimize vector databases, and manage Azure AI infrastructure.