Top Artificial Intelligence Jobs in Warsaw

Owns the full lifecycle of agentic AI solutions, from business problem framing and rapid prototyping through production deployment and continuous improvement. Builds agents capable of reasoning, planning, tool use, and enterprise integration. Develops evaluation strategies, guardrails, human-in-the-loop controls, and reusable components for regulated banking environments. Partners with business and technical stakeholders while optimizing quality, safety, latency, cost, and adoption.

Lead the engineering function on a remote consulting mission by setting technical direction, managing and mentoring engineers, driving the roadmap, overseeing complex delivery, improving engineering practices, and partnering with product and business stakeholders. The role requires hands-on technical leadership, architectural judgment, agile expertise, and evaluation of emerging technologies including cloud, AI, and blockchain.

Lead the engineering function for a growing technology company on a renewable consulting mission. Responsibilities include setting the engineering roadmap, managing and mentoring engineers, guiding architecture and technical decisions, leading complex projects, improving engineering practices, and collaborating with product and business stakeholders. The role requires hands-on technical involvement, strong software engineering expertise, and the ability to evaluate emerging technologies including cloud, AI, and blockchain. French fluency and strong English communication skills are mandatory.

Supports the Poland commercial team during pre-sales by conducting technical discovery, designing API-based solutions, creating tailored demos and presentations, and translating customer challenges into payment product solutions. Owns the technical customer lifecycle through deal closure, collaborates on upsell opportunities, delivers internal product training, and manages handoffs to post-sales implementation teams.

Build and own AI models, data pipelines, evaluation suites, and AI product features for construction procurement software. Develop document extraction and workflow automation using generative AI, LLMs, RAG, and optimization algorithms. Design complex data models, integrations, backend services, and production systems using Go, GraphQL, PostgreSQL, and AWS.

Build and deploy production-grade AI agents and generative AI tools for enterprise automation and analytics. Responsibilities include prompt design, tool integration, evaluation, Python software development, LLM and embedding implementation, cloud platform work, tested code, and Git-based collaboration. Nice-to-have experience includes vector databases, RAG pipelines, SQL, data pipelines, MLOps, Terraform, Docker, Kubernetes, and enterprise data privacy compliance.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Manages global programmatic, display, and video media campaigns from setup through optimization and reporting. Oversees targeting, bidding, pacing, tracking, attribution, audience segmentation, creative testing, and budget efficiency across DSPs, ad networks, publishers, and social platforms. Partners with analytics, marketing, creative, and technology teams to drive acquisition outcomes, ensure brand safety and privacy compliance, and improve campaign capabilities through data-driven strategies.

Build and support batch and streaming data pipelines, curated datasets, and Lakehouse platform capabilities. Responsibilities include data modeling, transformation, optimization, quality validation, reconciliation, testing, monitoring, and production support. The role partners with engineers and data consumers to deliver reliable data products for analytics, operational decision-making, and AI use cases.

Lead research and hands-on development for voice AI, focusing on real-time understanding and reasoning. Develop speech-to-text systems and multimodal large language models, advance existing fine-tuning and model architectures, and collaborate on data pipelines supporting product development. The role owns technical strategy and implementation while expanding the company’s commercial voice AI capabilities.

Lead the architecture and technical direction of backend AI systems for CKEditor. Design scalable distributed systems, build reliable LLM integrations, and establish testing, evaluation, monitoring, and reliability practices. Develop prototypes through production solutions, write and review code, mentor engineers, and influence engineering practices. The role requires hands-on ownership of complex technical challenges and collaboration across teams without formal management responsibility.

Build and launch customer-facing AI product capabilities from concept through production, measurement, and iteration. Partner with Product, Design, Data, Security, and platform teams to create reliable, measurable, trusted AI experiences. Responsibilities include evaluating probabilistic systems, designing failure paths, monitoring adoption and quality, supporting production readiness, and using customer feedback to improve, pause, or retire features.

Own AI platform capabilities from design through production operation, including LLM gateways, retrieval systems, agents, developer tooling, evaluation frameworks, and guardrails. Establish SLOs, observability, security, multi-tenant isolation, and reliable operational processes. Drive adoption through clean interfaces, migration paths, documentation, and reusable patterns while participating in on-call, incident response, and continuous improvement.

Design and deliver complex AI-powered automation systems using n8n, Make.com, HubSpot, JavaScript/TypeScript, and Python. Build integrations, AI agents, RAG systems, workflows, and custom applications involving APIs, databases, webhooks, authentication, LLMs, and vector databases. Own projects from requirements and architecture through deployment, troubleshooting, optimization, and documentation while collaborating with the consultancy team.

Build and maintain AI-powered insights platforms, including data pipelines, LLM and machine learning workflows, full-stack applications, APIs, monitoring, and cloud infrastructure. The role involves Python, Databricks, AWS, React, Terraform, Docker, and CI/CD. Engineers collaborate with product, data science, and business stakeholders, contribute to architecture decisions, write tested code, and deliver AI-generated recommendations to global business users.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Design, prototype, evaluate, and deploy AI agents and agentic workflows that improve global procurement processes. Partner with procurement, engineering, IT, analytics, governance, and external vendors to translate business needs into reliable enterprise solutions. Own solution delivery from discovery through rollout, including workflow design, integrations, observability, value tracking, risk management, and stakeholder communication. Build proofs of concept with low-code tools and guide scalable production implementations while ensuring privacy, compliance, auditability, and operational readiness.

Build and maintain business automations using n8n, Make, Zapier, APIs, and AI capabilities. Analyze and redesign workflows, collaborate with non-technical teams, support adoption, document reusable solutions, maintain reliability and security, and measure operational impact. The role also explores LLMs, RAG, and AI agents to reduce manual work across Marketing, HR, Finance, and Operations.

Create short films and videos using AI photo and video generation tools. Edit AI-generated content, develop concepts with marketing teams, maintain brand alignment, experiment with creative formats, and deliver engaging content for Tether and affiliated brands. The role requires video production and editing expertise, strong storytelling and visual composition skills, familiarity with digital marketing and social media, and the ability to manage multiple projects independently under tight deadlines.

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.

Own end-to-end product and operational analytics for AI-powered and conventional automation features. Analyze workflows, logs, transcripts, and generated outputs to identify failures, quality degradation, adoption patterns, and business impact. Design AI evaluations, human review processes, monitoring, dashboards, and experiments, then translate findings into product and engineering improvements. Partner with Product, Engineering, Clinical, MedOps, and Legal in an ambiguous, fast-moving medical technology environment.

Architect and lead implementation of an enterprise Generative AI Lakehouse platform on Databricks. Responsibilities include building document ingestion and structured extraction pipelines, enforcing anti-hallucination guardrails, developing Human-in-the-Loop review applications, integrating ERP feeds, and establishing governance, security, lineage, and auditability. The role also involves client consultation, architectural documentation, mentoring, and translating complex GenAI solutions for technical and executive stakeholders.

Build and operate production AI services, including multi-agent systems, LLM pipelines, MCP servers, RAG and document-ingestion workflows. Develop reliable Python backend services, evaluate model quality, manage deployments, observability, authentication and privacy safeguards. Collaborate with engineering and product teams while supporting AI governance, risk documentation and ISO evidence. The role focuses on practical business automation across document processing, customer support, CRM and account operations.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Develops World Vision International’s policy positions and external influence on children’s digital rights, AI governance, online safety, and digital participation. The role analyzes global regulatory developments, produces thought leadership and advocacy content, represents the organization in policy forums, leads coalition engagement, and advises internal teams and senior leaders. It requires collaboration across international teams and travel of up to 25%.