Top Artificial Intelligence Jobs in Warsaw

Lead design and implementation of scalable automation systems and integrations using GoHighLevel and tools like n8n/Make/Zapier. Build workflows for lead generation, nurturing, content creation, and sales pipelines; integrate CRMs with email, calendars, payments, and project tools. Maintain documentation (SOPs), advise clients, provide technical support, and own internal automation infrastructure to ensure reliability, scalability, and clear communication with non-technical stakeholders.

Lead design, build, and scale client-facing and internal automation systems. Create advanced workflows (GoHighLevel, n8n/Make/Zapier), integrate platforms via APIs/webhooks, document SOPs, advise clients, maintain CRMs and troubleshoot live systems for reliability and scalability.

Lead development of scalable AI-powered GTM systems, migrating from no-code to Claude Code agent architectures. Build integrations, data pipelines, and reusable agent frameworks; ensure reliability, observability, and cost optimization. Hire, mentor, and manage a distributed engineering team while evaluating emerging AI tools and driving platform innovation.

Manage and deploy AI-driven automation and workflows, onboard clients, translate requirements into actionable automations, design prompts for LLMs, troubleshoot and iterate systems, coordinate with AI engineers, and track project timelines and performance.

Build, launch, and optimize high-performance outbound campaigns and automated GTM systems using Clay, Claude, SmartLead, HeyReach, n8n, and APIs. Translate buying signals into targeted prospecting workflows, iterate on messaging and sequences, track CRM attribution, and optimize for pipeline outcomes and campaign KPIs (launch velocity, conversion, pipeline contribution).

Design, develop, and deploy AI/ML models and LLM-powered workflows (chatbots, copilots, automation). Integrate models with APIs and SaaS platforms, fine-tune prompts, work with structured/unstructured data, monitor performance, and collaborate with product and engineering teams to deliver scalable AI solutions.

As an AI Engineer, you'll design AI tools for authors, enhance internal workflows, and build tools for AI development, collaborating with teams to identify AI opportunities.

Design and build workflows using node-based AI systems for video and image generation. Collaborate with teams to enhance AI-driven processes and create demos for various stakeholders.

Build reusable AI developer tools, RAG knowledge systems, and AI-assisted SDLC workflows. Integrate coding assistants and design-to-code tooling, define secure observable patterns, and own reliability, usage, and cost for internal AI platforms.

Build and own end-to-end product features across backend and frontend. Implement Python services with SQLAlchemy/GraphQL/PostgreSQL, integrate external systems (GDS, payments, email/SMS), and use AI agents daily to plan, verify, and ship high-quality features.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.

As the AI Agents Solutions Architect at Kraken, you'll design and build an AI-native finance operating system, automating finance operations and ensuring compliance in a regulated environment.

The AI Video Editor / Motion Designer creates AI-driven videos to enhance advertising effectiveness. Responsibilities include video production, concept development, utilizing AI tools, performance analysis, and collaboration with team members.

Lead Oyster's data platform and AI strategy, centralize AI initiatives into production systems, build scalable data and MLOps infrastructure, modernize knowledge architecture and semantic search, partner cross-functionally to embed AI into products and workflows, enforce tooling standards and governance, and drive organizational adoption and change management for AI-assisted operations.

Build and scale core systems powering GenAI customer agents. Design reliable, high-performance distributed services, work across Java/Scala/Python stacks, use AI dev tools to accelerate engineering, ensure strong tests and observability, collaborate on architecture and product decisions, and deliver customer-focused solutions.

Build and maintain enterprise web applications using .NET and Angular, participate in full SDLC, integrate AI services and APIs, leverage AI-powered development tools and LLM/RAG solutions, contribute to architecture and technical decisions, collaborate with clients and delivery teams, and ensure compliance with enterprise/regulatory standards.

The AI Infrastructure Engineer will build and manage scalable model serving infrastructure for AI/ML applications, ensuring high efficiency and reliability in production.

Design, build, and maintain Claude-powered AI agents and modular multi-agent systems to automate bookkeeping and accounting workflows. Integrate with accounting platforms (Xero, QuickBooks, MYOB, etc.), implement human-in-the-loop processes, confidence scoring, audit trails, and continuous learning mechanisms, and collaborate with leadership to prototype and scale AI-driven accounting platform capabilities.

Lead product strategy and delivery for AI agent configuration and personalization features. Build admin and user-facing tools (personas, tone, permissions), collaborate with engineering and design, measure adoption and satisfaction, and iterate using customer discovery and data-driven validation.

Lead delivery of a multi-agent GenAI PoC for an FMCG/consumer health client: own client relationship, design solution architecture (Discovery, Ideation, Validation, Orchestration), drive evaluation and pilot, manage PoC milestones, present executive-ready materials, and identify Phase 2 opportunities.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

The role requires reviewing and evaluating AI-generated outputs and original content while applying local insights and maintaining quality standards. Strong analytical skills and attention to detail are necessary.

Lead two Gen AI teams to design, build, and deploy next-generation conversational agents. Manage roadmaps, mentor engineers, coordinate with product and business stakeholders, and integrate advanced LLM techniques and external APIs into production systems.

Review, evaluate, and annotate AI-generated text, images, audio, and video for accuracy and guideline compliance. Perform quality checks, identify edge cases, participate in calibration, and provide feedback to improve datasets and annotation workflows.