Top Artificial Intelligence Jobs in Paris

Designs and deploys enterprise AI-ready data platforms, data lakes, lakehouses, warehouses, pipelines, integrations, and sovereign data spaces. Works directly with customers to assess data ecosystems, identify AI opportunities, define transformation roadmaps, and deliver production-ready solutions and proofs of value. Requires strong expertise in distributed data systems, AI architectures, interoperability standards, cloud technologies, automation, CI/CD, DataOps/MLOps, security, governance, and consulting.

Own the vision, roadmap, and delivery of Implicity’s internal software ecosystem. Lead the back-office platform revamp, define agentic AI tools using Claude, MCP, and LLM applications, scale N8N automation workflows, and drive employee adoption. Conduct cross-functional discovery, translate operational needs into prioritized product initiatives, establish quarterly OKRs, and measure productivity impact across Engineering, Operations, Sales, Clinical, Regulatory, Customer Success, and Data teams.

Build and deploy production-grade LLM capabilities for the Kayzen Console. Responsibilities include developing AI-backed APIs and full-stack features, implementing RAG, embeddings, agents, and tool calling, and establishing evaluation, monitoring, observability, and feedback systems. The role optimizes quality, latency, reliability, and cost; troubleshoots production issues; collaborates with Product, ML, and Engineering; and turns prototypes into maintainable AI products.

Leads global privacy and AI legal matters for a SaaS employment platform. Advises Product, Engineering, Security, and business teams on privacy by design, AI governance, data protection, workforce data, incidents, regulatory compliance, vendor reviews, transfers, and contract terms. Builds scalable policies, controls, templates, training, and customer-facing trust materials while monitoring global privacy and AI regulations.

Build and ship full-stack features for a data intelligence SaaS platform, spanning backend services and frontend interfaces. Use AI coding assistants to accelerate development while applying sound engineering judgment. Participate in architecture discussions, code reviews, testing, incident response, troubleshooting, documentation, and knowledge sharing. Partner with product managers to translate requirements into technical solutions. The role emphasizes SaaS architecture, AWS cloud fundamentals, Docker, Kubernetes, CI/CD, agile delivery, autonomy, and production ownership.

Drive new business in Italy for MyTraffic by owning full sales cycles for Gini, prospecting outbound and inbound, engaging stakeholders, closing SMB and mid-market deals across Retail, Real Estate, and EV sectors, and identifying upsell opportunities while representing the company at industry events.

Sell Gini, an AI-powered location intelligence SaaS, across France. Own full sales cycle from prospecting to closing for SMB and mid-market, run demos and business cases, pursue upsell/cross-sell with Customer Success, and represent MyTraffic at industry events to grow market presence.

Lead full sales cycle for Gini, an AI-powered location intelligence solution across UK, Nordics, and Germany. Generate pipeline via outbound/inbound, demo product value to stakeholders, close SMB and mid-market deals, and drive upsell alongside Customer Success while representing MyTraffic at industry events.

Serve as a pre-sales applied AI architect partnering with GSIs and cloud providers (AWS/GCP) to develop joint GenAI solutions, codify reference architectures, support strategic customer deals, enable partner developer communities, and provide product feedback to inform roadmap and partner strategy.

Lead and build the marketing operations and agentic AI layer: define production standards for AI agents, deliver production-grade agents for lead scoring/enrichment/prospection/attribution, own martech stack and vendor decisions, report business outcomes to execs and board, hire and run a marketing engineering team, and cut tool costs while ensuring measurable revenue impact.

Build scalable, resilient, and secure backend microservices and APIs for production AI applications across AWS and Azure. Integrate databases, third-party services, legacy platforms, and AI systems; optimize performance for real-time workloads; implement authentication, authorization, RBAC, and rate limiting; and apply testing, CI/CD, Git, code review, and containerization best practices.

Build responsive, high-performance frontend applications for AI-driven enterprise solutions. Develop reusable components using modern frameworks, integrate REST APIs, WebSockets, and real-time streaming responses, optimize performance and state management, apply WCAG accessibility standards, write component-level tests, establish frontend engineering patterns, and collaborate with UX, backend, platform, and AI engineering teams.

Design and maintain automated testing strategies for AI-enabled applications across frontend, backend, APIs, data flows, and integrations. Build automation suites, validate LLM prompts and outputs, perform integration, regression, end-to-end, performance, and load testing, investigate defects, support root-cause analysis, and integrate quality standards and release gates with development and platform teams.

Designs end-to-end enterprise AI architectures on AWS, including LLM orchestration, integrations, cloud infrastructure, security, scalability, and governance. Leads technical discovery workshops, creates architecture documentation and standards, guides engineering squads, reviews designs, presents decisions to senior stakeholders, and evaluates third-party AI platforms for buy-versus-build decisions. Requires extensive senior architecture experience and fluent Dutch and English.

As a Senior Machine Learning Engineer, you will develop and scale customer-facing AI models, ensuring quality integration with business solutions, and mentoring peers.

Design, build, and deploy production-grade autonomous agents, multi-agent systems, and LLM-powered enterprise applications. Develop reusable orchestration patterns, integrate models with APIs, databases, tools, and enterprise systems, and implement structured outputs, memory, monitoring, tracing, evaluation, and recovery workflows. Deploy secure, scalable AI solutions primarily on AWS while applying MLOps and AIOps practices. Collaborate with engineering, data, cloud, and business teams.

Build and secure cloud infrastructure for production AI solutions across AWS and Azure. Responsibilities include designing CI/CD pipelines, implementing Infrastructure as Code, integrating security scanning and compliance controls, managing Docker and Kubernetes environments, configuring IAM and network security, monitoring and logging systems, improving reliability, and supporting penetration testing remediation.

Design and implement AI components for in-game event recognition and model optimization, focusing on multimodal learning and performance tuning.

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.

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.

Design and run AI-enhanced sourcing campaigns, maintain structured talent pipelines in Google Workspace, conduct market research and competitor mapping, automate repetitive tasks, ensure accurate data and excellent candidate experience, and evolve sourcing strategies using free LLM and automation tools.

Lead end-to-end deployments of LLM-powered autonomous agents into enterprise workflows, build custom integrations and data pipelines, collaborate with R&D to convert field feedback into product features, architect production-ready AI solutions for large clients, and serve as a technical consultant for stakeholders.

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.

Own technical customer relationships for Arango's AI product suite: run discovery, design graph and GraphRAG architectures, build prototypes, guide production deployment, define governance/monitoring, and enable customers while feeding product feedback.

Lead the AI platform that powers Photoroom's products: build an AI gateway, no-code tooling, and agentic multi-step visual workflows. Partner with engineers and researchers to turn model capabilities into reusable primitives, prioritize platform work across teams, and use data to define, measure, and iterate on shipped features.