Top Tech Jobs & Startup Jobs in Lille

Own end-to-end global customer implementations from kickoff through go-live and handover. Build project plans, establish governance, coordinate multiple countries and workstreams, manage risks, dependencies, RAID logs, milestones, and escalations, and lead client status meetings. Coordinate internal teams and client-owned actions, ensure go-live readiness, maintain project documentation, and support continuous process improvement. The role requires strong stakeholder management, communication, organization, and experience delivering complex multi-country implementations.

Build and improve a scalable data platform, including ingestion, transformation, warehousing, orchestration, governance, observability, and CI/CD. Audit the existing stack, establish data engineering standards, improve pipeline reliability and cost control, and deliver trusted datasets for product analytics, data features, and ML/AI use cases. Collaborate with Product, business teams, and company leadership on architecture decisions and strategic data initiatives.

Drive revenue and adoption of Zendesk’s AI products within a defined territory. Own sales quotas, prospect, conduct tailored demonstrations, support proof-of-concepts, and close new and expansion business. Partner with account executives, customer success, and regional leadership to develop sales strategies, identify cross-sell opportunities, model commercial value, and maximize automation-related revenue. Serve as an AI subject matter expert, enable sales teams, and communicate product updates and market insights.

Develop and improve semiconductor engineering software across UI, optimization workflows, C++ codebases, and AI integrations. Build MCP servers and agent pipelines that expose simulation tools to LLMs, while improving usability and reliability for scientists and technical users. The role also offers opportunities to launch and lead new software projects end-to-end. No prior simulation or optimization experience is required.

Build and grow Cloudera’s sovereign cloud business across EMEA. Develop relationships with sovereign cloud providers and enterprise customers, create marketplace offerings, drive partner enablement and sales motions, generate pipeline, and manage regional forecasts and bookings. The role requires expertise in enterprise cloud, data, AI/ML, sovereignty regulations, complex multi-stakeholder deals, executive communication, and cross-functional collaboration.

Own the full enterprise sales cycle for Cast AI’s cloud infrastructure automation platform in France. Responsibilities include outbound pipeline generation, opportunity qualification, value discovery, technical and business demonstrations, account mapping, tailored proposals, negotiation, closing, and coordinating value delivery with implementation teams. The role requires enterprise cloud SaaS sales experience, MEDDIC expertise, consistent outbound prospecting, and familiarity with Kubernetes, cloud, and DevOps technologies.

Manage and convert inbound EMEA SaaS leads (trials, enquiries, quotes, RFPs). Qualify and prioritise opportunities, demo product, recommend solutions, maintain CRM (HubSpot), follow up to close, and share customer/market insights with the team.

Design, build, and ship AI-powered product features from prototype through production. Own architecture, model selection, integrations, evaluation, reliability, cost, and latency. Work across frontend, backend, and infrastructure while establishing reusable AI development practices. Collaborate with engineering and product teams to define requirements, identify risks, and deliver maintainable, monitored, production-ready systems using LLMs, embeddings, RAG, vector databases, and multiple providers.

Lead and grow a backend engineering team operating with AI-assisted development. Own delivery quality and predictability, hiring, performance management, technical direction, and team development. Partner closely with Product, engage directly with freight customers, and help establish effective AI engineering practices, agent guardrails, review standards, and autonomous workflows. Remain hands-on approximately one day per week while improving engineering processes and outcomes across a distributed, remote-first organization.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.