Senior AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer (f/m/x) based in France.

This is a senior backend engineering role focused on building the internal AI infrastructure that enables an organisation to become truly AI-native.
You’ll take AI-powered tools from early prototypes through secure, reliable, and scalable production deployment.
The role combines backend engineering, AI/LLM applications, platform development, security, and internal product enablement.
You’ll work closely with senior technology leadership and engineering teams to assess opportunities, shape priorities, and deliver high-impact solutions.
A major part of the role involves creating reusable AI capabilities, governance frameworks, deployment pathways, and tools that can be adopted across the organisation.
You’ll have substantial autonomy and ownership in a remote-first, high-performance environment where decisions are driven by impact, experimentation, and strong technical judgment.
The position is open to candidates across Europe, including the UK, who have the right to work.

• Design, build, deploy, and operate reliable backend services, APIs, and integrations supporting internal AI applications and workflows.
• Develop secure and supported deployment pathways that allow non-engineering teams to launch internal AI tools with appropriate guardrails.
• Build shared AI capabilities, including reusable skills, plugins, MCP connectors, agent workflows, and a central registry covering internal tools, ownership, and costs.
• Develop company-wide AI services and standard tooling that help employees adopt AI effectively in their day-to-day work.
• Evaluate architecture, AI models, platforms, integrations, and build-versus-buy options using pragmatic technical and product judgment.
• Help define the technical direction, architecture, and scope of the internal AI platform.
• Establish risk-based review processes for internally developed AI applications and translate governance requirements into practical technical controls.
• Implement security safeguards covering identity, access control, sandboxing, model usage, secrets, and data handling.
• Move business-critical AI automations from individual machines and unsupported environments into reliable, maintainable infrastructure.
• Establish and continuously improve technical standards, runtimes, deployment practices, and engineering best practices for internal AI development.
• Partner with technology leadership and core engineering teams to turn AI strategy into scalable technical solutions.
• Drive adoption through demonstrations, documentation, integration support, and collaboration with departmental AI champions.
• Help teams overcome technical blockers and turn AI ideas into safe, maintainable, production-ready solutions.
• Maintain clear documentation so systems can be operated, maintained, and extended by other team members.
• Monitor developments in AI models, tools, coding assistants, and engineering practices, translating relevant advances into practical business opportunities.

Requirements:

• Significant senior-level experience building and operating production backend systems using Go, Python, or a similar programming language.
• Demonstrated experience owning services end to end, including architecture, deployment, secrets management, monitoring, reliability, and ongoing operations.
• Hands‑on experience building AI- or LLM‑powered applications for production use, with an understanding of model integration, evaluation, observability, and production failure handling.
• Familiarity with modern AI development tools and ecosystems, including AI coding assistants such as Claude Code, Codex, or Cursor.
• Understanding of emerging AI engineering concepts such as reusable skills, plugins, MCP integrations, agent workflows, and agent orchestration.
• Strong ability to evaluate technical options pragmatically and make sound decisions around architecture, model selection, integrations, and build-versus-buy.
• Excellent technical and product judgment, including the ability to simplify initiatives, challenge assumptions, or recommend against building when appropriate.
• Strong communication and collaboration skills, with the ability to work effectively with non-technical stakeholders and treat internal users as customers.
• A security-conscious engineering mindset, with an understanding of identity, access control, secrets, data exposure, and secure system design.
• Strong ownership, autonomy, curiosity, and willingness to experiment, learn from failure, and continuously improve.
• Google Cloud Platform experienc