Senior AI Engineer (f/m/x)

Accountabilities:: 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 experience is a plus. Strong Go experience, or strong Python experience combined with an interest in working with Go, is advantageous. Experience with product discovery, corporate IT, identity and access management, or application security is a plus. Experience supporting an organisation through an AI transformation is advantageous. Candidates must be based in Europe, including the UK , and have a valid right to work. Benefits: Fully remote-first working environment with the flexibility to work from your preferred location. Option to work from a well-equipped office in Vienna, including a dog-friendly environment. Flexible working hours and autonomy to organise your schedule around your work and personal commitments. Dedicated learning budget to support courses, conferences, and other professional development opportunities. Access to private sessions with experts supporting personal growth and mental wellbeing. Regular internal workshops focused on skills development, knowledge sharing, and cross-functional collaboration. Company-wide office weeks held three times per year, combining in-person collaboration, workshops, and team-building activities. Opportunity to work on high-impact AI initiatives and help shape the organisation’s transition toward becoming AI-native. Culture focused on ownership, open feedback, experimentation, knowledge sharing, and fact-based decision-making. Inclusive and collaborative international working environment. Opportunity to take on significant technical ownership while working closely with senior technology leadership and engineering teams.