Top Artificial Intelligence Jobs in Bucharest

Lead storytelling and communications for Pfizer's AI-native engineering transformation: set strategy, create content and live events, manage budgets and agency relationships, build cross‑functional engagement, track success metrics, and lead a storytelling team to translate engineering work for executives and broader audiences.

Lead EMEA Employee Relations, Labor Relations, and HR Generalist services. Define regional strategy, manage Works Council and union relationships, oversee investigations, optimize hybrid service delivery, drive transformation, implement data-driven tracking and AI-enabled insights, and partner with HR COEs and business leaders to support M&A and growth.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

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.

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.

Design, build, and operate an internal AI Background Agents Platform: implement secure stateful runtimes, sandboxing, CI/CD and GitOps pipelines, progressive delivery, observability (tracing/monitoring), and developer-facing tools to enable teams to build, test, and deploy autonomous LLM-backed agents.

Design and build LLM-powered agents to automate cybersecurity workflows within the Secure Software Development Life Cycle, with priority on vulnerability detection and remediation. Prototype, evaluate, and integrate agentic tools with SSDLC tooling, collaborate in Agile ceremonies, and share best practices on LLMs, agentic patterns, and cloud delivery.

Design and build the ALES platform AI core: architect agentic generative models to create and simulate realistic ATC scenarios from large flight and weather datasets, develop self-learning systems, integrate with production stacks, collaborate with ATC experts and cross-functional teams, and deliver scalable, tested deployments that improve V&V, training, and operational planning.

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.

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 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.

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 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.

Design, develop, and maintain automated tests (web, mobile, API) and integrate AI/LLM-driven testing tools. Analyze failures, maintain test data/environments, participate in code reviews, and report quality metrics while supporting automotive embedded and telematics domains.

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.

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.

Develop, deploy, and maintain machine learning models for operational defence and security systems. Work with data science teams to produce production-grade models using Python, SQL and ML frameworks, apply model deployment and MLOps practices, and integrate models into mission-critical systems.

Develop and maintain ETL/ELT processes, data platforms, and big-data pipelines that feed live European operations. Treat data as production code, enable data modeling and orchestration, and can grow into ML engineering within an AI track.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.

As an AI Research Engineer, you will optimize model serving and inference architectures, focusing on high-performance, resource-efficient solutions for AI systems across various deployment environments.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Provide administrative and operational support for the Data & AI organization by managing schedules, meetings, and team communications, and coordinating projects and onboarding activities.

Responsible for designing and maintaining an AI orchestration platform, overseeing AI solutions' integration, governance, and continuous improvement in collaboration with various stakeholders.