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Preply is a unicorn edtech platform (Series D, $150M) that connects 100,000+ tutors teaching 90+ languages to learners in 180 countries. The company is building human-led, AI-enhanced learning at global scale.
You will lead the GenAI and Agentic Platform teams within Preply's AI Platform organization. This is a multi-team engineering leadership role managing approximately 8–12 engineers across two complementary teams. The GenAI Platform owns shared model access, routing, evaluation, observability, prompt and configuration lifecycle, retrieval, grounding, and guardrails. The Agentic Platform builds on those foundations with durable execution, tools, state, context, memory, permissions, human controls, agent evaluation, and runtime safety. You will partner closely with a shared Product Manager and ML Platform leadership to shape strategy, priorities, and adoption.
Key responsibilities:
- Set long-term engineering vision for GenAI and Agentic Platforms, ensuring they operate as a coherent whole.
- Partner with Product Manager to define outcomes, prioritize investments, and measure platform impact.
- Lead and develop 8–12 engineers across two teams through clear expectations, feedback, performance management, career growth, and coaching.
- Own hiring quality, team composition, and operating models as platforms and company evolve.
- Guide architecture across model access, evaluation, observability, retrieval, agent orchestration, tools, state, memory, permissions, and control planes.
- Translate strategy into realistic plans, balancing foundational investment with near-term product needs.
- Align senior stakeholders across Product, Applied Science, Data, Security, and Engineering on platform standards and shared priorities.
You will not be the primary implementer but will go deep on architecture and production AI, coach senior engineers, shape platform abstractions and operational standards, and partner across functions.
REQUIREMENTS:
- 8+ years of software engineering experience, including 5+ years in engineering management and experience leading multiple teams or a multi-squad technical area.
- Track record of hiring, coaching, and retaining high-performing teams.
- Strong technical depth in platform engineering, backend or distributed systems, ML infrastructure, or developer infrastructure.
- Practical experience with production GenAI or Agentic systems; ability to reason about model access, evaluation, observability, retrieval, agent orchestration, tool use, state, permissions, reliability, cost, and safety.
- AI Expertise: Use Agentic AI beyond code generation to support architecture, planning, and decision-making while retaining human judgment for architecture, people decisions, business logic, and security; establish quality gates and safety nets for team workflows.
- Experience leading platform products with strong instinct for self-service, API design, developer experience, adoption, and avoiding unnecessary complexity.
- Clear communication and stakeholder leadership; ability to align teams with different incentives, make sound decisions with incomplete information, and revisit assumptions as ecosystem changes.
NICE TO HAVE:
- Experience managing teams that built AI or ML platforms used by multiple teams.
- Experience with agent frameworks or durable workflow technologies (LangGraph, OpenAI Agents SDK, Temporal).
- Hands-on familiarity with GenAI evaluation and observability, prompt or model lifecycle, retrieval systems, multi-provider routing, or open-model serving.
- Experience making build-vs-buy decisions without locking the organization into one provider or framework.
- Experience measuring platform success through adoption, customer outcomes, and engineering leverage rather than infrastructure delivery alone.
