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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 team building AI products and model inference systems. Requires 7+ years in technical leadership/management (AI/ML preferred) and prior hands-on engineering/research experience. Must have proven experience building/operating AI/ML platforms in production and strong fluency in model inference/serving infrastructure.

Core skills

model inferenceserving infrastructureAI/ML

Required skills

AI/ML platformmodel servingGPU workloadslatency optimizationcost optimizationmodel trainingmodel fine-tuningmodel evaluationproduction deploymentGPU schedulingbatchingquantizationlatency tradeoffsthroughput tradeoffsserving frameworksvLLMTritonproduction systemsreliabilityincident response

Optional skills

owning production systemsreliabilityincident 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.
  • Experience owning production systems, including reliability and incident response, is a plus.

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 an Equal Opportunity Employer and is committed to providing equal employment opportunities to all applicants without discrimination. We recruit on behalf of our clients and prohibit discrimination and harassment based on race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We are committed to a fair and inclusive hiring process. We process your personal data solely for recruitment purposes, in accordance with applicable privacy laws, and maintain reasonable safeguards to protect your information. Your data may be shared with our client(s) for hiring consideration, but will not be disclosed to third parties outside of the recruitment process.

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