Top Artificial Intelligence Jobs in France

Designs and implements enterprise AI and LLM solutions across Europe using Tencent Cloud TokenHub. Responsibilities include customer discovery, architecture design, POCs, technical validation, production deployment, troubleshooting, performance optimization, and technical proposals. The role develops scalable architectures using LLMs, RAG, AI agents, MCP, vector databases, fine-tuning, and cloud-native services while translating customer needs into platform enhancements and reusable implementation frameworks.

Own the end-to-end lifecycle, roadmap, adoption, and monetization of ArrowSphere’s AI portfolio, including the Assistant, AI 360 Dashboard, and AI Agents. Define AI product strategy, agentic use cases, pricing, packaging, recurring-revenue models, and value-added services. Partner with engineering, sales, marketing, finance, cloud vendors, and customers to deliver products, optimize commercial KPIs, support go-to-market initiatives, and enable internal teams and partners.

Designs, builds, evaluates, and deploys AI-powered software development workflows using Codex. Partners with engineering organizations to move prototypes into reliable production systems, improve developer adoption, and measure engineering productivity gains. Responsibilities include building integrations and evaluation harnesses, resolving implementation challenges, advising on security and operational readiness, leading technical workshops, and translating deployment insights into product and model feedback.

Designs, deploys, and governs production-grade agentic AI systems for enterprise clients. Responsibilities include multi-agent orchestration, RAG standards, multi-LLM integration, LLMOps, evaluation harnesses, observability, safety monitoring, cost controls, architecture sessions, reusable engineering patterns, and executive-facing impact measurement. The role also leads client engagements and manages, develops, and performance-manages engineering teams.

Leads AI and experience orchestration sales-overlay initiatives, supporting account teams with deal strategy, territory planning, pipeline creation, forecasting, customer workshops, proposals, pricing, enablement, and AI proof-of-concept execution. Serves as a senior AI subject matter expert for customer experience and conversational AI solutions, influencing executives and coordinating cross-functional teams across sales, marketing, product, customer success, and professional services.

Design, build, and deploy production-grade agentic AI systems, including multi-agent orchestration, RAG pipelines, LLM provider integrations, evaluation harnesses, observability, and cost and safety monitoring. Partner with client engineering teams on architecture, workshops, proofs of concept, and deployments. Develop reusable AI patterns, accelerators, and playbooks while measuring system accuracy, latency, safety, and cost-effectiveness.

Build and own full-stack features for Braiins Manager across TypeScript/NestJS services, PostgreSQL, Angular, React, distributed systems, and Kubernetes. Develop internal AI agent tooling involving MCP integrations, retrieval, orchestration, context engineering, and evaluations. Troubleshoot production systems at scale, write robust tests, and collaborate independently in a fully remote international team.

Develops and validates AI/ML models for fiber test and measurement applications. Owns the end-to-end machine learning and signal-processing lifecycle, including data collection, preprocessing, feature extraction, model development, optimization, proof-of-concept and MVP validation, deployment, and production integration. Applies filtering, spectral analysis, noise characterization, statistical modeling, and time-series analysis to fiber network data while collaborating with international cross-functional teams.

Lead Fever’s AI search strategy by measuring brand visibility across LLMs and emerging platforms, testing how SEO signals influence citations, and developing analytical frameworks for AI visibility reporting. Collaborate with Product and Engineering to optimize schemas, site architecture, and APIs for AI ingestion. Evaluate new AI models and tools, translate developments into experiments, and execute PR and community strategies that strengthen brand authority and LLM perception.

Build and deploy production-grade AI solutions for clinical research: select and orchestrate LLMs, implement RAG and agentic systems for multimodal medical data, create scalable pipelines, and collaborate with cross-functional teams to integrate AI features that support patient recruitment and site selection.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Provides strategic legal support across intellectual property, IT, technology transactions, commercial contracts, privacy, cybersecurity, and digital transformation. Drafts and negotiates international agreements, manages IP protection and disputes, advises stakeholders on legal risks, supports compliance and governance, monitors regulatory developments, and delivers internal training. The role requires strong commercial judgment, communication, negotiation, and stakeholder management in an international environment.

Support Value Engineering by analyzing customer process data, identifying use cases in the Celonis platform, quantifying financial impact, preparing management presentations, and presenting insights to C-levels while leveraging Celonis AI and data modeling.

Leads global commercial customer data governance, Customer 360 strategy, segmentation, data quality, reporting, and insight initiatives. Owns customer definitions and hierarchies across SAP and Salesforce, establishes governance and KPI standards, and aligns reporting and analytics investments with business value. Partners cross-functionally to improve data quality, reporting adoption, forecast accuracy, and AI readiness while driving change management and value realization across the commercial organization.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Own and negotiate commercial contracts, including MSAs, DPAs, SaaS agreements, and vendor contracts. Partner with Sales, Customer Success, and leadership to support go-to-market activities, manage risk, and accelerate deal cycles. Build scalable legal templates, playbooks, and processes while advising on data protection, compliance, and corporate matters. The role requires pragmatic commercial judgment in a fast-paced B2B SaaS environment with international US/EU contracts.

Own product marketing for Cyara’s Agentic AI assurance products, including positioning, messaging, go-to-market launches, competitive intelligence, sales enablement, technical content, and cross-functional collaboration. The role targets enterprise buyers through sales-led motions and requires measurable pipeline impact, strong writing and presentation skills, and comfort working with technical teams. Experience in AI, contact centers, QA, testing, observability, or monitoring is advantageous.

Advise CIOs, CDOs, and AI leaders on data modernization, analytics, and AI adoption. Lead solution design, architecture, proposals, demonstrations, proofs of concept, and technical pre-sales for complex transformation engagements. Translate business goals into scalable data and AI strategies while collaborating with hyperscalers and technology partners. Guide governance, security, compliance, machine learning, generative AI, and advanced analytics initiatives for multinational customers.

Own end-to-end infrastructure delivery for strategic physical AI customers, from discovery and architecture through production rollout. Build cloud compute orchestration, platform services, onboarding environments, observability, security, and cost controls for simulation, training, inference, and batch workloads. Debug across infrastructure layers, productize recurring customer needs, and shape the physical AI platform roadmap. Partner with customers, Field CTO, Product, and Engineering while using AI coding tools to accelerate production engineering.

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.

Set technical direction across engineering squads, leading Azure architecture, API management, cloud reliability, observability, infrastructure, and developer experience. Design standards and reusable frameworks for agentic AI, chatbots, MCP integrations, security, token-cost governance, and scalable product capabilities. Mentor teams, align engineering and data science, and drive modernization through robust APIs, event-driven systems, and maintainable AI ecosystems.

Build Python-based backend services, APIs, and integrations that embed AI capabilities into a SaaS platform. Develop scalable customer-facing features, connect AI outputs to workflows and dashboards, collaborate with product, design, and platform teams, and implement observability, monitoring, and error handling. Contribute to the AI integration stack, including SDKs, MCP servers, and LLM orchestration.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Gather client requirements and architect, develop, and deploy cloud data platforms, warehouses, ETL processes, pipelines, APIs, and BI solutions. Perform advanced SQL and data modeling, support deployments and integrations, diagnose technical issues, mentor staff, contribute to innovation and practice development, and assist with project management. The role requires approximately 20% overnight travel and primarily in-person work.

Lead the design, build, and deployment of AI-powered agents, workflows, and integrations for global marketing. Evaluate buy-vs-build, integrate platforms (HubSpot, Salesforce, Meta, Google, LinkedIn), optimize AI economics, and measure ROI while collaborating with marketing teams to automate and improve campaign execution and content localization.