Engineering Manager - AI Product(100% Remote EMEA)

Location: Remote (Europe Time Zone) Start date: ASAP Language: English Team: AI

Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI Engineering Manager to lead the small, high-leverage team behind their AI product.

The Engineering Manager is to lead a team of AI engineers and researchers building the systems that power an AI-enabled products and the model inference offering. You’ll manage the people and the roadmap: hiring and developing a high-caliber team, setting technical direction alongside senior ICs, and driving delivery on projects that range from applied ML features inside the products to the infrastructure that serves models in production at scale.

This is a hybrid people/technical leadership role. You should be comfortable running a team day-to-day (1:1s, planning, performance, hiring) while also being comfortable enough technically to review designs, unblock research and engineering tradeoffs, and represent the team to other engineering and product leaders.

• Manage, coach, and grow a team of AI/ML engineers and researchers, including hiring, career development, and performance management.
• Own delivery for AI-enabling projects across the product portfolio, translating ambiguous product and research goals into scoped, sequenced engineering plans.
• Co-own the roadmap and operations of the inference offering, including reliability, latency, cost, and scaling of model serving infrastructure.
• Partner with research scientists to move promising models and techniques from experimentation into production, balancing research rigor with shipping velocity.
• Set and maintain engineering standards for the team: code quality, experimentation practices, evaluation methodology, on-call, and incident response for production inference systems.
• Work closely with Product, Infrastructure, and Data teams to prioritize work and remove cross-team blockers.
• Report on team progress, risks, and capacity to engineering leadership, and represent the team’s work in planning and roadmap discussions.
• Stay current on the AI/ML and inference landscape (models, serving frameworks, hardware) and bring relevant developments back to the team’s technical strategy.

• 7+ years of experience in a technical leadership or engineering management role (AI/ML teams preferred), plus a strong prior track record as a hands-on engineer or researcher.
• Proven experience building and operating AI/ML platform or inference infrastructure in production (model serving, GPU workloads, latency and cost optimization)
• Working knowledge of the AI/ML lifecycle: model training or fine-tuning, evaluation, and production deployment.
• Experience with, or strong technical fluency in, model inference and serving infrastructure (e.g., GPU scheduling, batching, quantization, latency/throughput tradeoffs, serving frameworks such as vLLM, Triton, or similar).
• Demonstrated ability to manage both researchers and engineers, who often have different working styles, timelines, and definitions of “done.”
• Strong judgment on scoping and sequencing ambiguous, research-adjacent projects into shippable increments.
• Excellent communication skills; able to translate technical tradeoffs for both engineers and non-technical stakeholders.
• Experience owning production systems, including reliability and incident response, is a plus.

• Own a product, not a component: Lead the team behind the company's AI product and shape the capabilities the wider business builds on
• High leverage, small team: With three engineers, your technical and strategic decisions translate directly into what ships
• Grow as a leader: Manage, mentor, and inspire a talented team while influencing strategic technical decisions
• Stay hands-on: Balance leadership with coding in a modern, high-scale AI platform environment
• Work with cutting-edge technology: Deepen your expertise in LLMs, inference infrastructure, GPU compute, and distributed systems at scale
• Drive platform evolution: Directly impact architecture, reliability, and AI quality across the organization
• Collaborate across teams: Work closely with Product, Infrastructure, Security, and Backend teams, expanding your cross-functional expertise
• Remote-first flexibility: Enjoy a fully remote role while aligning with the European time zone