Top Artificial Intelligence Jobs in Hungary

Provide customer support for brands through social media and email, ensuring prompt responses and engaging service. Flexible hours and remote work.

Design, build, and maintain automated test suites, evaluation scenarios, metrics, and datasets for AI-powered features. Automate QA workflows with Python and CI/CD, test APIs and ML model outputs, define quality strategy and acceptance criteria, create CI/CD quality gates, mentor teams, participate in code reviews, and document findings.

Lead engineering enablement across eight companies to cascade CTO AI vision into team discipline. Detect and package successful practices, run cross-company diffusion, operate cadence of validation and demos, measure adoption and outcomes, triage deeper needs to PoCs/workshops, and capture reusable artifacts and metrics.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Design, build, test and deploy AI-powered agentic workflows using a low-code/no-code platform. Translate customer processes into reliable LLM-driven automations, write and refine prompts, analyze outputs, customize workflows, and collaborate with engineers and stakeholders.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Lead and scale enterprise Automation and AI across GBS Shared Services. Define strategy, oversee global delivery of RPA, low-code and AI/ML solutions, ensure governance, drive ROI, partner with finance and operations workstreams, build team capabilities, and manage portfolio, budgets, and KPIs.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Build end-to-end AI features and prototypes across backend and frontend, prototype AI agent use cases, create UI/blueprints/examples to make AI workflows usable, and ship features quickly in collaboration with product and backend teams.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

Lead full life-cycle development of cloud-native SaaS TMS solutions: prototype, design, implement front-end (React) and back-end (.NET/C#) systems, deploy to Azure with CI/CD, optimize performance and scalability, and use AI-assisted tools to accelerate delivery.

Design, build, and run production agentic workflows and reusable components for delivery processes. Implement RAG-backed knowledge bases, monitoring, evals, observability, and human-in-the-loop feedback to improve agents and integrate them with delivery teams and business tools.

Lead architecture and hands-on development of an AI-native underwriting platform. Design scalable backend services in Python, integrate with React/TypeScript frontends, promote engineering standards, implement observability and security, and use AI-assisted development tools to improve productivity while mentoring the team and driving the platform from MVP to production.

Design, build, deploy, and operate scalable, secure AI and LLM-based platform services on AWS. Develop reusable libraries, infrastructure as code, CI/CD pipelines, and observability. Collaborate with applied scientists and product teams to productionize AI capabilities, ensure security and privacy, and drive platform-wide best practices for reliability, cost efficiency, and governance.

Own product vision, roadmap, and strategy for AI digital platforms; manage end-to-end content operations and governance; define OKRs/KPIs; translate business needs into user stories; collaborate with UX/UI, development, analytics, and stakeholders; improve UX and lead planning, testing, and releases.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

Work remotely as a Hungarian (hu_HU) C2 speaker to conduct voice-mode conversations with AI chatbots, pursue predefined goals, and rate interactions. Use your smartphone for voice input and a laptop to complete written evaluations in English, following detailed project guidelines and confidentiality rules.

The Principal Data & AI Consultant leads data-related projects, manages revenue targets, supports sales efforts, and coordinates with teams to deliver integrated AI solutions while ensuring client satisfaction and account growth.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

We seek a Senior Python Engineer to manage technical objectives, lead development on data pipelines and AI/ML systems, and mentor junior engineers.