Top Artificial Intelligence Jobs in Romania

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 QA Network Engineer will test AI datacenter networking solutions, focusing on SONiC systems, smart NIC integration, and performance for AI workloads.

Lead a small engineering team in R&D to validate new product concepts quickly. Responsibilities include technical vision, fullstack development, light research, team motivation, and partnership with product and design teams.

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.

Build and deploy production-ready ML and Generative AI solutions: develop LLM-powered apps, implement RAG pipelines and vector DB integrations, train and deploy ML models, integrate AI via APIs, and operate AI workloads in cloud/on-prem environments with monitoring and guardrails.

Lead horizon scanning and external intelligence to identify AI and disruptive tech opportunities for R&D. Translate trends into actionable briefs, design and run pilots with stage-gates, and scale successful capabilities into production. Influence senior leadership with strategic foresight, build external partnerships, and embed a future-back innovation culture across cross-functional teams to measurably improve R&D outcomes.

As a Customer Support Expert, you will provide customer support via social media and email, representing various brands while setting your own schedule and working remotely.

Create high-volume, high-quality marketing content using generative AI and AI agents. Produce video, image, and social content, develop attention-driving campaigns, track AI and culture trends, and iterate quickly with the marketing and founding team.

Lead AI-native engineering: build and ship production-grade features, convert AI-assisted prototypes into reliable systems, own architecture/security/quality, direct AI coding agents, define engineering standards, and work closely with founders on product and technical strategy.

Build features, prototypes, and demos using modern AI coding tools and agents; iterate prototypes into reliable, scalable production; direct and evaluate AI coding agents; collaborate closely with founders and senior engineers; explore and improve AI development workflows to accelerate product delivery.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.

Develop, deploy, and optimize Python-based Generative AI and Agentic AI applications. Build LLM integrations, design autonomous agent workflows, implement retrieval pipelines (RAG), prompt engineering, and integrate with enterprise APIs. Collaborate with cross-functional teams, apply best practices for testing, monitoring, and deployment, and leverage vector databases and Elasticsearch where applicable.

As an AI Operations & Automation Specialist, you will optimize finance and HR operations through automation, AI implementation, and process improvement while ensuring data integrity and supporting various teams in the company.

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.

Design and deliver AI-enabled product solutions for financial services clients, acting as product owner to define scope, prioritize value, and simplify processes. Use AI daily to speed analysis, design, documentation, and testing while collaborating with cross-functional teams to build reusable, UX-first features and reduce delivery complexity.

Join the AI & Innovation team to build and maintain full‑stack Python services, integrate ML/LLM models into production, develop scalable APIs and data pipelines, optimise AWS infrastructure, and write unit/integration tests to ensure reliability for high‑traffic jobseeking products.

Lead the design and delivery of AI-enabled full-stack applications, ensuring solutions meet enterprise standards while mentoring other engineers.

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.

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.

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.

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.