Top Artificial Intelligence Jobs in Budapest

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Design, build, and maintain production-grade Python APIs and backend services (FastAPI); develop, deploy, and optimize LLM applications (OpenAI, Anthropic); implement end-to-end RAG with vector databases and semantic search; build MCP servers, multi-agent systems, event-driven architectures, and messaging; create and refine prompts and agents; monitor, secure, and scale AI infrastructure while collaborating across teams.

Design, build, and optimize cloud-based Databricks data platforms and scalable ETL/streaming pipelines (Delta Lake, Spark). Collaborate with data scientists and stakeholders, troubleshoot performance, and support analytics and MLOps workflows on Azure.

As an AI Solutions Architect, you will design scalable AI architectures, evaluate technical feasibility, define product requirements, provide mentorship, and assess AI models for enterprise deployment.

The role involves implementing AI features, improving retrieval quality, collaborating with teams, and building backend APIs for various projects.

Lead sales pursuits for private cloud AI solutions, build and manage pipeline, collaborate with account managers, develop pursuit plans, engage clients up to C-level, contribute to proposals and negotiations, drive renewals, and use Siebel for forecasting and deal management. Requires vertical industry knowledge and regional language skills.

Identify and validate high-value AI use cases for financial services, lead discovery workshops, build ROI-driven business cases, map and redesign workflows, define technical requirements and acceptance criteria, prototype solutions with no-code tools, implement AI governance and ontologies, and ensure business-aligned delivery and compliance.

The Head of Performance will lead performance marketing strategies, focusing on optimizing paid acquisition channels and utilizing AI tools for data-driven decisions.

The Architect will design and build AI products, manage full product lifecycles, and lead teams in creating innovative software solutions.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

The AI Platform Engineer will configure and evolve enterprise AI platforms, develop APIs, ensure reliability of AI services, and support CI/CD processes.

The AI Solution Engineer translates AI opportunities into solution designs, implements AI use cases, and coordinates with stakeholders to ensure compliance with architectural standards.

The AI / Machine Learning Researcher will conduct applied research, develop prototypes, and work with data to create AI-driven features related to home design.

The Senior Data Scientist will own the ML lifecycle, design AI services, implement MLOps practices, and mentor team members in production ML capabilities.

Lead and build the AI foundation for an AI-native vulnerability management platform. Own AI strategy, evaluation frameworks for non-deterministic agents, fine-tuning and model-routing experiments, prototype and ship agentic features, and lead a small hands-on AI team to productionize breakthroughs in generative AI for cybersecurity.

Design, build, and operate production-grade automations that reduce manual work across Operations, Support, Finance, and Tech. Identify high-volume automation opportunities, integrate with existing systems via APIs/webhooks, apply AI/LLMs for classification/routing/summarization, and ensure reliability, observability, and iterative improvement of workflows.

The Software Engineer will develop AI applications for customer experience using full-stack skills, handling features end-to-end, and collaborating with various stakeholders.

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.

Develop and deploy production-ready Generative AI applications using LLMs and RAG. Integrate OpenAI/AWS Bedrock APIs into systems, collaborate with data engineering, tune performance, monitor deployments, and document solutions for technical and non-technical stakeholders.

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.

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.

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.

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.

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

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.