Top Artificial Intelligence Jobs in Paris

As an AI Engineer, you will build AI agents for preventive health, focusing on reasoning, clinical workflows, and ensuring reliable production systems.

The Applied AI Engineer will develop automated MLOps pipelines for integrating and deploying AI models in healthcare robotics, ensuring compliance with regulations and achieving clinical accuracy targets.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

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.

Provide legal counsel on AI, privacy and data protection across customer, partner and supplier contracts; lead EU AI Act readiness and ISO 42001 alignment; advise on IP, data transfers, DPIAs, incident response, audits and regulator engagement; produce playbooks, training, and negotiation support across commercial teams.

Act as primary technical contact in pre-sales for large-scale GPU and AI projects: analyze AI workloads, design and provision custom GPU clusters, run POCs, translate constraints into business value, and collaborate with sales and engineering to close enterprise deals.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

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.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Seeking a Senior Software Engineer to build AI inference systems. Responsibilities include optimizing GPU kernels, architecting inference stacks, and defining benchmarking methodologies. Requires strong programming skills and experience in ML systems.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Design, scope and govern modular, secure Power Platform and Copilot solutions. Lead architecture workshops, audit environments, produce HLD/LLD, supervise implementations, manage technical teams, and define AI/Copilot standards and best practices.

Design and develop scalable .NET software architectures, integrate generative AI/ML services (Azure AI, OpenAI, ML.NET), lead technical workshops, mentor developers, enforce CI/CD/DevOps practices, conduct code reviews, and ensure software quality and security.

Lead and deliver change workstreams on complex transformation programmes, build multi-stakeholder adoption strategies, measure impact with KPIs and analytics, disseminate an augmented consultant model and AI agents, develop offerings and adoption kits, manage and upskill consultants, and support executive governance and client relationships.

Lead and deliver AI and data transformation engagements from strategy to implementation. Design automation and Infrastructure-as-Code solutions, mentor teams, manage change, and present to clients. Work in multidisciplinary teams on generative AI, intelligent platforms, and large-scale digital transformations.

Lead change management workstreams combining frameworks, employee experience design, and AI agents; conduct impact studies, design adoption strategies, run workshops, deploy governance and reporting, support pre-sales, mentor consultants, and contribute to R&D of change products and AI modules.

Lead design and delivery of scalable .NET service-oriented architectures, integrating generative AI (Azure AI, OpenAI, ML.NET). Provide technical leadership, mentor teams, run workshops, enforce DevOps/CI-CD, code quality and security practices, and drive technology adoption across projects.

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, and deploy production LLM- and agent-based systems that automate medical coding in hospitals. Own end-to-end AI features from research and prototyping to deployment and monitoring. Build secure health-data ingestion pipelines, integrate AI outputs into clinical applications, and define the AI roadmap with the CTO.

The role involves performing data-related tasks supporting AI content improvement in French, including data collection, evaluation, annotation, and object tagging.

Lead the design and delivery of AI agents, automations, and internal tools for People workflows; train and enable non-technical teams; partner with Engineering on data, security, and infrastructure; define responsible People AI policies; measure adoption and impact and run an AI Champions program.

Lead development of an autonomous agentic AI scientist for drug discovery: architect multi-step reasoning agents, bridge AI and wet-lab experiment design, prototype to productionize agentic systems, publish research, and collaborate with biological experts.

Perform human review and annotation tasks to train and evaluate AI: generate or assess content, correct text, analyze multimedia, provide voice recordings, and deliver structured annotations consistent with guidelines and cultural context.

Lead strategic account growth by positioning Nagarro as the AI transformation partner to CXOs, deliver 15%+ YOY revenue growth, shape CXO agendas, manage procurement and legal negotiations, collaborate with internal engineering and AI capability teams, and secure client references and testimonials.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.