Top Artificial Intelligence Jobs in Bucharest

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

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.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

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.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

Own the AI agenda across Customer Operations by identifying, implementing, monitoring, and optimizing AI features such as chat and email agents. Manage multiple concurrent projects, align stakeholders, translate operational pain points into automation opportunities, and improve processes across Customer Support and Payments, Fraud & Verification. Track post-launch performance, resolve issues, and drive continuous operational excellence through analytical, creative, and cross-functional problem-solving.

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.

Design and build agentic AI systems that analyze ServiceNow Discovery logs, failures, metrics, and infrastructure telemetry at enterprise scale. Develop agents for failure classification, root cause analysis, corrective-action recommendations, observability, and reusable troubleshooting workflows. Integrate OpenAI and Anthropic APIs using RAG and vector databases, while applying testing, guardrails, and human approval. Build production-grade Python services, REST APIs, data pipelines, integrations, and CI/CD automation, supported by strong infrastructure and network troubleshooting expertise.

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.

Design, build, deploy, and maintain ML/DL models and AI agents; productionize prototypes, integrate AI into enterprise systems, provide 3rd-level support, follow ITSM processes, and ensure ethical and regulatory compliance while collaborating with cross-functional stakeholders.

Lead definition and governance of global enterprise technology architecture to create secure, resilient, and AI-ready platforms. Design cross-environment infrastructure (on‑prem, hybrid, multi‑cloud, edge), enforce architecture standards and guardrails, assess AI workload readiness, drive migration and modernization roadmaps, reduce technical debt, and provide architectural direction, coaching and stakeholder alignment across security, DevOps, vendors and business teams.

Lead end-to-end product backlog for procurement interoperability and orchestration across source-to-pay. Design integration and data alignment across procurement platforms, run stakeholder workshops, translate demand into user stories and releases, manage E2E testing, rollout and BAU transition, and embed AI-driven automation and prompt-driven workflows to improve efficiency.

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.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

As an AI Inference Engineer, you will optimize C++ systems for AI model inference on edge devices, collaborating with researchers to deploy and enhance models while ensuring runtime stability and performance.

Lead design and implementation of agentic workflows, multi-agent collaboration and AI-to-AI systems. Drive R&D in explainable AI, federated learning and privacy-preserving techniques, integrate AI solutions into core platforms, mentor junior engineers, and ensure ethical AI practices.

Define technical vision and roadmap for the Ask.ai platform, select models and infrastructure, set standards and governance, coordinate AI engineers and contributors, design integrations and platform architecture, ensure security and data privacy, and provide technical mentorship and reusable components to accelerate AI solutions across teams.

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.

Sell Libra AI to Romanian small/mid-size law firms and in-house legal teams. Manage full sales cycle from inbound/outbound prospecting to demo, negotiation, and close. Collaborate with Legal Engineering, Customer Success, and Marketing to tailor demos, onboard customers, maintain pipeline, and meet ARR targets using data-driven outreach and sales methodologies.

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.