Top Artificial Intelligence Jobs in Bucharest

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.

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.

The Lead AI Engineer will design and implement enterprise AI platforms, focusing on integrations, automation workflows, and performance optimization, ensuring secure adoption across the organization.

The Chief Data & AI Officer will lead the establishment of a company's data and AI infrastructure, ensuring reliable information capture, decision-making processes, AI system integration, and compliance with governance standards.

The Senior Data Engineer will design and maintain data pipelines, develop ETL processes, optimize GCP services, ensure data quality, and collaborate with stakeholders.

The BI Engineer will create and maintain dashboards, support analysis, ensure data integrity, and contribute to data strategy initiatives.

Design, build and maintain AI-embedded Regulatory News applications across the full Agile development lifecycle. Define AI best practices, collaborate with product owners, perform design and peer code reviews, improve code quality, support releases, and reduce operational workload through AI-driven features.

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.

The Senior Data Engineer designs and maintains data pipelines and AI workflows, optimizing ETL processes for BI and LLM applications.

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

Own the AI platform roadmap and build reusable capabilities (prompting, RAG, tool calling, agents, evaluation, observability). Run discovery, prioritize AI investments, partner with Product, Engineering, Design and Data, guide other PMs, define success metrics, and ensure scalable, reliable AI-powered features that deliver customer and business value.

The VP of Business Development will drive commercial growth in Europe, focusing on strategic opportunities with renewable energy stakeholders and building relationships to enhance market presence.

Design, develop, and maintain AI and generative models (LLMs); build and support reliable, performant AI systems; craft and optimize prompts; collaborate with cross-functional teams from scoping through release; contribute to engineering and product discussions and experimentation.

Lead design and governance of ICON's end-to-end AI platform, multi-agent frameworks, and supporting services. Define cloud-native, scalable architectures, integration patterns, APIs, and standards; lead solution architecture, design reviews, and mentor engineering teams to deliver secure, high-performing AI/ML production systems.

Manage end-to-end release lifecycle for a multi-agent AI platform: own release calendar, plan and orchestrate feature/patch/hotfix deployments, coordinate cross-functional teams, enforce quality gates and compliance, monitor release performance, run post-release reviews, mitigate risks, and lead release communications and escalations.

Lead QA for AI platforms by defining test strategy, automation, and quality governance. Design AI-specific and CI/CD-integrated test frameworks, validate agent behavior, manage QA team, enforce quality gates, drive metrics and continuous improvement across engineering and product teams.

Lead development and operationalisation of Responsible AI frameworks and compliance processes. Translate regulations (EU AI Act, GDPR) into controls, implement risk assessment, bias detection, model validation, embed governance in development lifecycles, manage audits and incident response, and drive stakeholder engagement and training.

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.

Manage and grow a Bucharest-based test automation team for automotive telematics. Own test automation strategy and execution for TCU validation across vehicle, backend, and mobile domains. Plan automation activities, define scalable frameworks, track KPIs, drive AI-assisted testing innovation, ensure compliance with automotive quality standards, and coordinate with global stakeholders and suppliers.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

Post-sales technical lead for strategic EMEA accounts, advising on cloud-native and AI deployments. Own technical relationships, troubleshoot escalations, design architectures for LLM/agentic workloads, drive product adoption, deliver training, and feed customer insights to Product and Engineering.

Own global go-to-market strategy and positioning for SUSE's AI portfolio. Translate technical cloud-native, containerized, and edge inferencing capabilities into executive-level messaging, create high-value content, enable sales and partners, lead ecosystem marketing, and provide market and competitive intelligence to influence product and GTM decisions.

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, build, and own AI/LLM-assisted product features in Ruby on Rails: integrate LLM APIs, combine AI with business logic, tests, fallbacks and safeguards, improve reliability/latency/cost/security, write automated tests, and debug production issues.