Top Artificial Intelligence Jobs in France

The Strategy Execution Consultant manages client relationships, designs solutions linked to strategy, leads projects, and facilitates workshops to drive business results.

As a PhD Investment & Strategy Associate, you'll conduct research and financial analysis focused on AI-driven technology companies, providing insights for investments while collaborating with a talented team to support strategic decision-making.

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.

Build and own an AI-native content production stream: design experiments with Acquisition, produce generative-video ads, synthetic voices and AI-driven edits, scout and implement tools, document pipelines, and scale localized, conversion-ready assets while capturing institutional learnings.

Support mapping and improving SDLC practices to identify AI-assisted use cases across requirements, development, testing, release, and run. Design risk-aware frameworks, controls, and guidance for responsible AI in delivery. Run experiments, prepare playbooks, KPIs, and communications, and collaborate with project managers, architects, developers, security, and data/AI teams to accelerate IT delivery while preserving quality, security, and governance.

Lead AlixPartners' AI Transformation practice in France: define AI strategy, identify high-value use cases, prototype and deploy AI solutions (PoCs/MVPs), drive adoption, measure business impact, build methodologies, support business development and mentor colleagues.

Design and build reproducible, containerized cloud platform challenges covering networking, IAM, observability, deployments, scalability, and disaster recovery. Develop automated validation tests, reference and defective solutions, debug environments, and document architecture and validation logic.

Join the GenAI team to develop LLM-powered features for pricing and operations. Design experiments, perform prompt engineering, build evaluation frameworks, benchmark models, analyze failure modes, and document results for production-ready solutions supporting revenue management.

Act as the technical bridge between AI/analytics capabilities, customers, and sales across EMEA. Identify use cases, run discovery workshops, demos, pilots and PoCs, enable sales via content and training, feed product/R&D with field insights, and support product launches. Role requires regular travel across EMEA and close collaboration with HQ.

Build and own internal AI platform surfaces and infrastructure end-to-end: Cortex UX, platform services, deployment pipelines, observability, governance, and developer tooling to enable teams and agents to build and operate AI-powered features.

Lead and own Agent0: co-own roadmap with Product, hire and grow a senior AI engineering team, drive delivery of production-grade agentic AI, set evaluation and monitoring standards, prototype innovations, and provide thought leadership on AI production excellence.

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.

Build end-to-end AI features and prototypes across backend and frontend, prototype AI agent use cases, create UI/blueprints/examples to make AI workflows usable, and ship features quickly in collaboration with product and backend teams.

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.

Lead multiple engineering teams to deliver scalable, reliable AI search and discovery products. Own delivery, execution, and operational excellence; coach engineering managers; shape roadmaps with Product and Design; drive system design, scalability, and performance; and contribute to senior technology leadership and organizational planning.

Review and validate neuroscience research, case studies, and AI-generated content; create clear explanations, annotations, and scenario-based exercises; identify errors and inconsistencies; apply current neuroscience methods and provide structured, evidence-based feedback to improve content quality for AI training.

Review biochemical datasets, protocols, and literature to evaluate AI-generated content for scientific accuracy. Develop realistic scenarios and training materials, identify errors or missing context, provide structured, evidence-based feedback, and explain complex biochemical concepts clearly. Participate in iterative content review and validation to improve AI understanding of life science topics.

Review and validate pharmacology content, create realistic cases and structured datasets, evaluate AI-generated pharmacology responses, identify errors and missing context, provide evidence-based feedback, and translate complex pharmacological concepts into clear training materials while documenting methodology and collaborating with multidisciplinary teams.

Lead design and delivery of AI-native customer experience platforms, combining frontend architecture, LLM ecosystems, retrieval/agent orchestration and production delivery. Mentor a small engineering team, prototype and ship AI-enabled products, advise clients, run discovery and workshops, and drive AI-augmented engineering practices and governance.

Twelve-month apprenticeship supporting internal digital change and AI awareness communications. Drafts and formats English content, manages intranet and Viva Engage communities, assists event production (webinars, townhalls), creates visuals and short videos, and helps simplify AI topics for non-expert employees while contributing to editorial planning and communication workflows.

Lead short-term AI adoption program: build internal AI champions, create usage policies and training, support teams implementing AI tools, contribute to internal AI tool builds, and ensure responsible, secure deployment across distributed teams.

Lead and coach an enterprise sales team to drive AI-powered business process transformation using Copilot and agent orchestration. Develop go-to-market and partner strategies, build C-level relationships, manage pipeline and forecasting, scale AI CRM/ERP solutions, and ensure sales execution and consumption targets while sharing customer successes and driving continuous improvement.

Build and maintain integrations across AI frameworks, MCPs, SDKs, and developer platforms. Ship plugins, connectors, templates, and agent tooling that let developers access Nimble. Contribute to open-source, publish examples, engage developer communities, and support partnerships and events to drive adoption.

Lead end-to-end implementations of QVAC-based AI deployments, act as primary client contact, translate business needs into deployment strategies, coordinate cross-functional teams, define roadmaps and governance, track multiple concurrent projects, and produce executive reporting and documentation for production rollouts.

Review, evaluate, and annotate AI-generated text, images, audio, and video for quality, consistency, and guideline compliance. Perform quality checks, identify edge cases, participate in calibration activities, and provide feedback to improve datasets and annotation workflows for multilingual AI projects.