Top Artificial Intelligence Jobs in Poland

Creates technical documentation, implementation guides, whitepapers, product content, landing pages, blogs, and specifications covering AI infrastructure, GPU computing, cloud systems, enterprise hardware, cybersecurity, and related technologies. Translates complex technical information into clear content for IT professionals, engineers, architects, and decision-makers. Collaborates with technical and product experts, researches emerging technologies, validates accuracy, and maintains consistent documentation standards.

Own and advance the evaluations platform for InPost’s production conversational AI shopping assistant. Responsibilities include LLM-judge pipelines, evaluation datasets, Polish-language golden sets, root-cause analysis, abuse and anomaly detection, reproducible release gates, and eval-driven development. The role provides technical leadership, establishes platform direction, mentors engineers, collaborates with product and business stakeholders, and translates quality goals into measurable definitions.

Perform project accounting, revenue recognition, financial analysis, reconciliations, forecasting, and month-end reporting across a global portfolio. Partner with project and finance teams to ensure accurate reporting under US GAAP and IFRS. Use Power BI, Power Query, Copilot, and automation tools to improve processes and data quality. Support finance transformation initiatives and implementation of the IFS Cloud ERP platform, including testing, documentation, issue resolution, and post-go-live stabilization.

Build and deliver full-stack product features using AI coding agents, owning requirements, architecture, implementation, testing, deployment, monitoring, and incident response. Review agent-generated code and documentation, improve team prompts and guardrails, maintain production reliability, and contribute to a strong engineering culture. The role requires commercial experience with PHP, Node.js, or Golang; JavaScript, TypeScript, React, SQL, Docker, cloud technologies, AWS, CI/CD, testing, and technical documentation.

Design, train, and evaluate large multimodal and vision-language-action models for robotic agents. Develop reinforcement and imitation learning methods, embodied datasets, simulation environments, world models, planning systems, and sim-to-real experiments. Build robust research software and distributed training infrastructure, validate approaches on physical robots, and collaborate with research and engineering teams to deploy reliable systems. Communicate findings through technical reports, open-source releases, demonstrations, and publications.

The Data and AI Product Manager will develop and execute a data product roadmap, prioritize AI use cases, gather requirements, ensure data governance, and manage stakeholders to drive data-driven decision-making in tourism.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Translate and localize content between Polish and Lithuanian, preserving cultural nuance, accuracy, tone, and contextual relevance. Edit language content, apply terminology standards, provide structured feedback to improve language models, and support quality assurance for digital tools and applications. Collaborate with production and cross-functional teams as an independent contractor with flexible scheduling and project-based availability.

Develop and maintain structured technical content optimized for human and AI consumption. Manage metadata, taxonomies, search synonyms, prompt libraries, and content governance for generative AI and digital channels. Improve voicebot accuracy through phonetic lexicons and ASR model refinement, analyze user feedback, and provide stakeholder training on AI tools and content practices. The role requires expertise in technical documentation, conversational AI, NLP, knowledge management, and AI-supported content delivery.

Design and build production-ready AI solutions, including RAG pipelines, autonomous agents, and MCP integrations. Shape AI architecture, infrastructure, scalability, and reliability while integrating enterprise data. Participate in Scrum planning, conduct code reviews, and maintain documentation and testability. The role requires deep Python expertise, distributed systems knowledge, container orchestration, databases, caching, observability, and LLM orchestration frameworks.

Deliver live workshops and hands-on labs teaching professionals to use generative AI for visual, video, document, interactive, and automated content production. Demonstrate tools and workflows, provide structured feedback, and help learners create brand-consistent deliverables. Collaborate with curriculum teams to develop templates, exercises, case studies, and course materials while continuously improving instruction based on learner feedback and AI industry developments.

Build Python-based backend services, APIs, and integrations that embed AI capabilities into a SaaS platform. Develop scalable customer-facing features, connect AI outputs to workflows and dashboards, collaborate with product, design, and platform teams, and implement observability, monitoring, and error handling. Contribute to the AI integration stack, including SDKs, MCP servers, and LLM orchestration.

Audit and assess a voice AI platform integrating Twilio, real-time LLMs, and AWS services. Review call bridging, media streams, session logic, APIs, background jobs, schemas, reliability, capacity, alerting, and incident response. Deliver a findings report and prioritized implementation roadmap, then provide part-time advisory support on architecture, webhook contracts, telephony integrations, prompt design, and production operations.

Build and maintain AWS-based data pipelines and lifecycles (Glue, DMS, Redshift, S3). Develop production data transformations and CDC using Scala and Python, automate CI/CD with Bash, optimize Spark jobs (partitioning, Parquet, broadcast joins), and deliver reliable, idempotent pipelines while collaborating remotely with cross-functional teams.

Develop and own production-ready machine learning, LLM, NLP, and RAG solutions within Palantir Foundry and AIP. Responsibilities include data exploration, model development, evaluation, deployment, monitoring, workflow integration, and optimization for accuracy, scalability, reliability, latency, and cost. Collaborate with engineers and business stakeholders, make architecture decisions, translate business needs into AI solutions, and communicate model behavior and limitations.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.

Develop production-grade full-stack web applications powered by large language models and agentic AI systems. Build AI agent workflows, search and retrieval services, ingestion pipelines, vector indexing, responsive interfaces, monitoring dashboards, and scalable performance infrastructure. Implement authentication, authorization, data protection, audit logging, and regulatory controls. Collaborate with AI developers, data scientists, and stakeholders while managing multiple priorities in a fast-paced environment.

Design and deploy AI-driven features, autonomous agents, and scalable workflows for Cisco Webex Partner Hub. Build production systems using LLMs, vector databases, and agentic frameworks; establish standards for evaluation, prompt engineering, reliability, security, latency, and cost efficiency. Collaborate with product and data science teams, evaluate emerging AI technologies, architect cloud-based platforms, and mentor junior engineers while guiding technical initiatives.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Analyze production Voice AI behavior, transcripts, logs, and operational data to identify failures, quality changes, and business impact. Build AI evaluation frameworks, monitoring systems, and dashboards; measure reliability, efficiency, and patient experience; and translate findings into product improvements with Product, Engineering, QA, and Operations teams.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Lead the design, build, and deployment of AI-powered agents, workflows, and integrations for global marketing. Evaluate buy-vs-build, integrate platforms (HubSpot, Salesforce, Meta, Google, LinkedIn), optimize AI economics, and measure ROI while collaborating with marketing teams to automate and improve campaign execution and content localization.

Lead the design and delivery of production conversational AI systems, including multi-turn agents, LLM reasoning loops, and multi-agent orchestration. Use Python, Azure, MLflow, and Databricks to build and maintain end-to-end AI solutions. Mentor scientists, lead cross-functional initiatives, promote AI best practices, collaborate with customers, and guide adoption of conversational AI across enterprise sustainability use cases.