Top Artificial Intelligence Jobs in Budapest

Serve as a technical-strategic partner for AI Decisioning customers, leading use-case delivery from discovery through go-live and expansion. Collaborate with engineers, executives, marketers, and IT stakeholders to define requirements, explore customer data, recommend marketing improvements, manage project risks, and develop delivery best practices. The role also contributes to AI Decisioning product strategy and requires customer-facing consulting, strong communication, and 10–25% travel.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

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.

Lead analysis and visualization of complex datasets to support pricing, product, customer, market, supply chain, inventory, and operational decisions. Develop executive reporting, scalable data models, self-service analytics, and AI-enabled data quality capabilities. Investigate discrepancies, improve processes, define data requirements, and collaborate with global cross-functional teams. Translate complex insights for technical and non-technical audiences while mentoring junior analysts and driving continuous improvement.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Manage multi-country payroll operations, compliance, audits, controls, vendor relationships, payroll analysis, and process improvements. Lead payroll system automation and scalability initiatives while ensuring accurate and timely processing across jurisdictions. Partner with finance, HR, treasury, and external providers, monitor regulatory changes, and mentor a global payroll team in a distributed technology environment.

Lead a small engineering team building and shipping AI-powered SaaS features. Set technical direction, establish standards for observability, testing, security, scalable architecture, and AI evaluation, while managing delivery timelines and team development. Remain hands-on by designing and implementing production AI systems using LLMs, embeddings, RAG, vector databases, and related tooling. Partner with Product and leadership on prioritization, architecture, resourcing, and risk management.

Support AI governance and data privacy compliance across Syngenta. Responsibilities include implementing OneTrust and AI governance workflows, conducting privacy and AI risk assessments, supporting vendor due diligence, advising on compliance controls, monitoring GDPR and EU AI Act developments, handling queries and incidents, and creating policies, training, and awareness materials.

Leads end-to-end architecture for enterprise data, analytics, and AI solutions in a Microsoft-first environment. Translates business requirements into secure, scalable designs; guides prototyping, implementation, reviews, troubleshooting, and production readiness. Requires deep Azure data platform, Power BI, enterprise security and governance, Azure OpenAI, and RAG experience. The architect provides hands-on technical leadership and ensures solutions meet operational, compliance, cost, and supportability standards.

Join Welo Data’s Hungarian contributor network for flexible, remote AI data projects. Depending on project needs, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create and test prompts for large language models; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Build and maintain PHP and Laravel backend services and APIs for a major product release. Own features from design through deployment and monitoring, integrate agentic AI workflows and LLM-based tooling, optimize performance and reliability, improve security, and mentor engineers. Collaborate independently with a cross-functional team on ambiguous technical challenges while delivering production-ready software.

Build and ship production voice-first agentic AI systems. Responsibilities include LangGraph agent workflows, tool calling, memory, backend integrations, real-time speech pipelines, latency optimization, interruption handling, observability, evaluation, testing, architecture, and product collaboration. The role requires strong Python and software engineering skills, production GenAI experience, and may involve voice technologies such as Pipecat, LiveKit, WebRTC, STT, and TTS.

Build and own production agentic AI runtime components, including context construction, retrieval and tool orchestration, ranking, scoring, guardrails, multilingual quality, latency and cost optimization, and evaluation systems. Diagnose production failures through traces and improve agent reliability for customer-facing commerce applications.

Lead transformation programs for documentation platforms, systems, and workflows. Manage roadmaps, milestones, dependencies, risks, requirements, and cross-functional workstreams across content, engineering, UX, and IT. Support Agile delivery, stakeholder alignment, vendor collaboration, governance, adoption of new tools, and continuous improvement. Drive automation and AI-enabled documentation solutions using data-informed performance monitoring and feedback loops.

Build and ship agent orchestration workflows, integrations, and shared infrastructure for AI-driven growth across paid media, lifecycle, organic content, CRO, incentives, and referrals. Implement monitoring, audit logging, creative generation pipelines, and reliable integrations so domain experts can tune and operate workflows independently.

Build and operate enterprise AI platform services, APIs, SDKs, agent runtimes, retrieval systems, evaluation frameworks, observability, guardrails, and governance controls. Lead architecture for scalable, secure, reliable cloud-native services; write production Python code; establish testing, CI/CD, and operational practices; and drive complex technical initiatives. Mentor engineers, shape platform roadmaps, and potentially assume broader people leadership as the team grows.

Drives AI marketing strategy and transformation for enterprise customers. Owns AI Decisioning use cases from discovery through launch and expansion, leads customer design sessions, documents requirements, manages technical projects, mitigates risks, builds stakeholder relationships, and identifies campaigns or optimizations that improve outcomes. Partners closely with engineers, product teams, marketers, executives, and IT stakeholders while contributing to AI Decisioning product strategy.

Design and deploy AI microservices and LLM-powered applications using Python, REST/gRPC, Docker, and Kubernetes. Build RAG, hybrid search, agent, fine-tuning, quantization, evaluation, and prompt-guardrail systems. Monitor model quality, latency, cost, and security while integrating databases and SIEM/SOC platforms. Establish MLOps, testing, observability, and compliance standards for high-security public-safety environments. Collaborate with security teams on CJIS and FedRAMP audits, with optional travel to Japan and the United States.

Join Welo Data’s Swedish AI Trainers Network as a flexible, remote contributor. Participants may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and review cultural and linguistic accuracy for AI systems. This is a talent community rather than an active opening. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation.

Join Welo Data’s remote Kyrgyz contributor network for potential AI data projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, or chatbot responses; create prompts for large language models; and review cultural and linguistic accuracy. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. This is a talent-community opportunity rather than an active job opening.

Join Welo Data’s Tamil contributor network for potential remote AI projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Projects vary in length and compensation, with details provided before each assignment.

Join Welo Data’s Romanian contributor network for flexible, remote AI projects. Potential work includes annotating text, images, or audio; evaluating search results, advertisements, and chatbot responses; creating prompts; and reviewing cultural and linguistic accuracy. Applicants need native or near-native Romanian, English proficiency, digital tool comfort, attention to detail, and residence in Romania or Moldova. This is a talent network rather than an active opening, with project scope, timelines, and compensation provided when opportunities arise.

Join Welo Data’s remote Bosnian AI contributor network to support flexible projects involving text, image, or audio annotation; search, advertising, or chatbot evaluation; and prompt creation for large language models. Contributors help improve linguistic, cultural, and industry-specific accuracy in AI systems. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Bosnian, English proficiency, digital-tool comfort, and strong attention to detail are required.

Join Welo Data’s contributor network for potential flexible, remote AI projects involving text, image, and audio annotation, search and chatbot evaluation, prompt creation, and cultural or linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. Applicants must be English-fluent, detail-oriented, comfortable with digital tools, and based in Malaysia, India, the Philippines, or Indonesia.