SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Preply is a unicorn edtech platform (Series D, $150M) that connects 100,000+ tutors teaching 90+ languages to learners across 180 countries. The company is building human-led, 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/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—you'll write production code, shape platform abstractions and operational standards, and partner across 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 so teams can build agents without re-solving runtime infrastructure
- Evaluate frameworks, workflow engines, and tool protocols while operating the platform with clear SLOs, capacity and cost controls, incident response, and operational standards
The role offers significant ownership in a small team, direct influence on system architecture and technical direction, and the opportunity to shape the future of agentic AI at Preply.
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 expertise as a forefront user of Agentic AI; ability to influence architecture, business logic, and security beyond code generation; experience using AI as a thought partner and setting 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; willingness to join a paid on-call rotation
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
