Top Artificial Intelligence Jobs in Romania

The role involves designing and deploying AI systems for clinical operations, developing models for decision-making, and ensuring AI implementation aligns with data governance standards. Responsibilities include collaborating across teams, enhancing operational efficiency, and advancing AI applications in a regulated environment.

Lead design and deployment of AI agents and workflow automations across Supply & Operations, coach and lead Operational Excellence (Lean/Six Sigma) projects, build OE capabilities, embed continuous improvement and AI-driven workflows into enterprise systems, and lead global OE programs and strategies in External Supply.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Lead global payroll strategy and transformation for 30,000 employees across 56 countries, driving AI/RPA and middleware integrations, ensuring SOX and global data/tax compliance, consolidating vendor ecosystem, aligning payroll with Total Rewards and Finance, and upskilling the global payroll delivery team.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead management and optimization of Crayon and Clozd platforms, integrate them with CRM and sales enablement systems, drive cross-functional adoption, execute win-loss programs, monitor platform metrics, and deliver actionable competitive and buyer insights to improve win rates and product roadmaps.

The CSM Transformation PMO Lead will manage the transformation roadmap, oversee governance across initiatives, and partner with stakeholders to ensure successful change implementation.

Design and implement user-facing features from concept through implementation, combining UX design and front-end engineering. Build, iterate, and maintain UI/UX and business logic to drive engagement and conversion, collaborate with product/marketing/support, participate in code reviews, and leverage modern tools and deployment workflows.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Designs and implements AI, automation, and analytics solutions for supply chain. Develops data models, governance, reporting, and advanced analytics; collaborates with process owners to enable data-driven decisions and trains/supports business users.

Lead end-to-end technical projects for a Voice AI CX platform: scope, plan, manage releases, align product to customer requirements, track metrics, ensure quality, and communicate status to clients and engineering.

Provide hands-on stabilization of multiple early-stage, often AI-generated codebases: assess, fix bugs, refactor, add missing core functionality (auth, payments), improve performance, implement lightweight testing, and collaborate across teams on fractional hourly engagements.

Own SEO strategy and KPI progress for client accounts, build AI-supported workflows and automations, create repeatable SEO processes, lead client communications and reviews, and drive measurable visibility and business outcomes by combining AI tools and specialist expertise.

Lead full‑stack development of high‑traffic public websites, integrate AI tooling into the SDLC, design scalable backend and performant UIs, maintain cloud infrastructure, CI/CD, monitoring, and testing, and own services under a you‑build‑it‑you‑run‑it philosophy.

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.

Lead applied research and system design for agent-native search: develop multi-stage retrieval, ranking, and grounding methods for LLMs working with real-time web data; define evaluation paradigms; optimize relevance, latency, and cost; deploy solutions to production and mentor the engineering team.

Lead hands-on applied AI work: prototype demos, accelerate customer POC-to-production, perform technical onboarding, optimize distributed training and inference on GPU infrastructure, research and implement emerging ML techniques, and feed actionable product feedback while producing reusable assets and benchmarks.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.

The AI Applied Scientist Intern will tackle complex problems using deep learning, statistical analysis, and large datasets, collaborating with a team to implement AI solutions that generate economic impact.

Produce narrative-driven long-form AI-generated videos end-to-end: concept, prompting, generation, editing, compositing, motion graphics, color correction, and maintaining character/style continuity using emerging AI video tools.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

Lead a cross-functional squad to architect and ship AI-native workflows, integrations, and experimentation infrastructure that scale growth. Build data frameworks, attribution and analytics stacks, run rigorous A/B programs, package repeatable AI enablement toolkits, and collaborate with Engineering to deploy agentic product surfaces.

Develop and maintain open-source, silicon-optimized AI/ML inference application packages (Inference Snaps) for Linux/Ubuntu Core. Debug, write high-quality code, review upstream contributions, secure and optimize local inference deployments across embedded devices to gateways, and collaborate with a distributed team and stakeholders.

The role involves providing legal guidance on global privacy and AI issues, collaborating with teams to ensure compliance, and developing scalable processes.