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Pragmatike

Engineering Manager - AI Product

RemoteEMEA· UTC-1…UTC+3
Published
Role
Engineering Management
Experience
Lead
Employment
Full-time
Salary not disclosed
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Open to Anywhere in EMEA · UTC-1…UTC+3. Set where you work from to check your eligibility.

No BS summary

AI Engineering Manager needed to lead a small, high-leverage team building AI products and model inference systems. Requires hybrid people/technical leadership, managing a team, roadmap, and technical direction. Must be comfortable with day-to-day management and technically reviewing designs.

Core skills

model inferenceserving infrastructureAI/ML

Required skills

model servingGPU workloadslatency optimizationcost optimizationmodel trainingmodel evaluationproduction deploymentGPU schedulingbatchingquantizationlatency tradeoffsthroughput tradeoffsserving frameworkscode qualityexperimentation practiceson-callincident response

Optional skills

owning production systemsincident response

Required languages

English

What you'll do

  • 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.

What they require

  • 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.

Benefits

  • 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

Pragmatike is recruiting on behalf of a global leader in mobile payment and digital content monetization. The client operates across 60+ countries, connecting telecom operators, merchants, content providers, media companies and brands, powering Direct Carrier Billing, Mobile Money, Local Payment Methods, content distribution, interactivity programs and multi-channel activations.

FintechStartup
Salary not disclosed