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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 AI-enhanced learning experiences at global scale.
The Agentic Platform team sits within Platform Engineering and builds shared infrastructure for creating and operating reliable AI agents. This team works closely with GenAI Platform (model access, evaluation, observability, retrieval) and ML Platform (traditional and predictive ML) to compose foundations into a runtime and developer experience for stateful, action-taking AI systems.
As a Senior ML Platform Engineer, you will build production infrastructure that takes agent prototypes to production, solving distributed-systems problems in long-running, non-deterministic workflows. This is a hands-on senior role with broad technical influence where you'll write production code, shape platform abstractions and operational standards, and partner with Applied Science, Data, Product, Security and Engineering teams.
Key responsibilities:
- Build a durable agent runtime with checkpoints, retries, timeouts, resumability, and deterministic recovery
- Create a secure tool layer for discovery, registration, invocation and versioning across internal APIs and external services (including MCP)
- Own agent state, context and memory primitives with clear lifecycle, privacy, retention and retrieval semantics
- Design identity, scoped permissions and human controls for authorization, approvals, escalation and handoffs
- Develop guardrails for tool access, policy enforcement, argument validation, sandboxing and action limits
- Provide end-to-end observability, trace replay and scenario-based evaluation across plans, model calls, tool calls, state transitions and outcomes
- Ship SDKs, templates, local tools, documentation and paved-road patterns for teams building agents
- Evaluate frameworks, workflow engines, and tool protocols while operating the platform with clear SLOs, capacity and cost controls
You'll work in small teams with significant ownership, directly shaping system architecture, technical direction, and platform evolution. The role includes a paid on-call rotation.
REQUIREMENTS:
- 5+ years proven track record designing, building, and operating backend services or ML infrastructure handling production traffic
- Strong Python skills and experience building developer-facing APIs/SDKs or shared libraries
- Experience building GenAI-powered or agentic systems using tool/function calling, structured outputs, and multi-step workflows
- Hands-on experience as a forefront user of Agentic AI; ability to influence architecture, business logic, and security decisions; use AI as a thought partner; set up quality gates and safety nets
- Experience integrating production services through APIs and events, including authentication, authorization, and secure service-to-service interaction
- Experience with at least one major public cloud and its services/infrastructure (preferably AWS)
- Hands-on experience with distributed tracing, system telemetry, SLOs, and incident triage
- Strong communication skills and C1 English level
NICE TO HAVE:
- Experience with agent frameworks or durable workflow technologies (LangGraph, OpenAI Agents SDK, Temporal)
- Experience with agent evaluation, simulation, or production feedback loops
- Experience designing sandboxed execution environments and delegated authorization for autonomous systems
- Hands-on experience with MCP Gateway
- Familiarity with GenAI observability and model gateways
