Top Artificial Intelligence Jobs in Warsaw

Drive research applying advanced ML (Transformers, GNNs, diffusion models) to semiconductor design and optimization; implement algorithms in Python/C++ using PyTorch; prototype and validate approaches, publish in top conferences, collaborate with engineers, and contribute to EDA tool integration.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Design, build, and optimize AI-driven automation workflows using LLMs, no-code/low-code platforms and custom APIs. Integrate CRMs and internal systems, develop Python/JavaScript backend logic, monitor performance, and collaborate with stakeholders to scale automated processes.

Lead and scale demand generation by building signal-driven, automated GTM systems using AI and no-code tools. Own MQL-to-pipeline metrics, optimize CAC, run performance campaigns, integrate CRM and enrichment workflows, collaborate with sales/RevOps to improve conversions and pipeline ROI.

Lead engineering to shift GTM from no-code automation to code-first, AI-agent-driven systems. Design scalable backend pipelines, integrate CRMs/APIs, build reusable agent frameworks, ensure reliability and observability, and hire/mentor a distributed engineering team to deliver production GTM infrastructure.

Remote SDR responsible for outbound prospecting, qualifying leads, booking demos, maintaining CRM records, collaborating with marketing and sales, and meeting monthly KPIs in the AI SaaS space.

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 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.

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.

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.

Own and scale AI enablement: build core orchestration, LLMOps/MLOps platforms and governance, integrate generative AI into product, optimize cost/latency, run PoC-to-production delivery, upskill teams, standardize tooling and vendor strategy, and track adoption/ROI metrics.

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.

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.

As an AI Creative Producer, you'll develop and scale AI-generated content across various platforms, collaborate with teams, and enhance production workflows.

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.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.

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.