Top Artificial Intelligence Jobs in Romania

Create high-volume, AI-assisted conversion copy across full funnels—landing pages, sales pages, email sequences, VSL/webinar scripts—and product messaging. Build and maintain prompt libraries and AI workflows, run A/B copy tests, optimize hooks/headlines/CTAs, and collaborate with design, sales, and product teams to drive measurable conversion lifts.

Lead end-to-end delivery of AI-enabled products as a hands-on Technical Project Manager and business analyst: scope, schedule, documentation, UAT, governance, KPI tracking, and automation to accelerate engineering throughput and stakeholder alignment.

Convert raw workshops, interviews and long-form video into high-volume micro-content, sizzles, courses and high-converting landing/funnel pages using AI tools. Manage asset libraries, QA, reporting, CRM integrations and rapid revisions to meet SLAs.

Design high-converting email templates and marketing assets in Go High Level, maintain modular visual systems for web, social, ads and funnels, run A/B tests, package specs for hand-off, and introduce AI tooling to accelerate workflows while ensuring accessibility and performance.

Build, optimize, and scale high-converting sales funnels using GoHighLevel and AI tools. Implement A/B tests, conversion optimization, retargeting campaigns across major ad platforms, ensure tracking and integrations, write conversion-focused copy, and deliver measurable improvements in conversion rate, ROAS, and revenue.

Design and define end-to-end scalable, resilient AI architectures (data pipelines, model training/serving, retrieval, monitoring, governance), collaborate with delivery teams, contribute to proposals, mentor engineers, and evaluate emerging AI tools and technologies.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

Lead AI productivity platforms, ensuring enterprise-wide adoption and compliance. Oversee platform governance, integration, and performance measurement while driving AI operational models and risk management in a regulated environment.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

Lead AI architecture and implementation for financial services clients: support business development, enable and manage engineering teams, design scalable LLM/multi-agent systems, ensure AI safety, compliance, and monitoring, and translate business needs into technical specifications.

The role involves leading design for AI-native products at Synthesia, focusing on improving interaction patterns and enhancing user experience in AI-driven workflows.

The role requires deploying AI systems to enhance sales processes across Flosum's go-to-market teams, focusing on automation and pipeline efficiency. Responsibilities include training AI agents, integrating systems, and optimizing workflows for revenue generation.

The AI Engineering Intern will design, test, and deploy scalable AI systems, integrate models, and work on inference optimization, collaborating with data scientists on complex problems.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

AI Engineers at QuantCo design, build, and implement applied AI systems, working with data scientists to optimize inference, develop scalable solutions, and integrate AI into enterprise operations.

Lead enterprise AI strategy, operating model, governance, platform enablement, and CoE to deploy safe, compliant, and scalable AI across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions in a regulated pharmaceutical environment.

The AI Solutions Manager drives strategy and commercialization of AI solutions, focusing on scalable solutions, partnerships, and sales enablement.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Design, build, and maintain cloud-native AI platforms and infrastructure; develop, deploy, and optimize AI agents and agentic runtimes; enable teams with AI-assisted development and automation; collaborate with engineers and AI specialists to deliver scalable, secure, production-ready AI solutions.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

Lead end-to-end development and integration of AI features (LLMs/ML) into web/mobile apps and APIs. Design AI-first UX, craft and optimize system prompts, build agentic workflows (LangChain/CrewAI/AutoGen), implement error-handling and hybrid cloud/on-prem deployments, and collaborate within product squads using Agile/Scrum.

Lead design, build, and operate a multi-tenant AI platform and LLMOps infrastructure across cloud and on-prem. Own vector DBs, feature stores, model hosting (Kubernetes + GPU orchestration), and developer self-service tooling. Standardize LLM-as-a-service offerings and enable squads with APIs, templates, and documentation.

Design, develop, fine-tune, and deploy ML and NLP models (including MT and LLM finetuning). Own projects end-to-end using Python, TensorFlow/PyTorch, Docker, MLflow, and AWS; perform statistical analysis, monitor production models, document experiments, and collaborate across teams.

Define product vision and strategy via market research and data analysis; build prioritized roadmaps; collaborate with PMs, designers, and engineers to launch products; communicate with stakeholders; track performance and iterate post-launch.

Perform guided evaluations of filters and options on desktop and mobile to ensure relevance to customer queries. Follow guidelines, conduct online research, complete qualification tests, and maintain accuracy and consistency. Work remotely as a freelance data rater in Swedish, completing 5–15 flexible hours weekly.