Senior ML Platform Engineer (Agentic Platform)

We power people’s progress.

At Preply, we’re all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact.

We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we’re only getting started. As a category-defining company, we’re shaping what the future of learning looks like at global scale.

Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.

Meet the team!

The Agentic Platform team sits within Platform Engineering. We build shared infrastructure and abstractions that help product and engineering teams create and operate reliable AI agents. Our scope includes durable execution, tools, context, memory, permissions, approvals, failure recovery, debugging, and control.

We work closely with GenAI Platform, which provides shared model access, evaluation, observability, and retrieval, and ML Platform, which supports traditional and predictive machine learning. Agentic Platform composes those foundations into a runtime and developer experience for stateful, action-taking AI systems.

We work in small teams with significant ownership, empowering you to directly shape system architecture, technical direction, and platform evolution. Learn more through our Engineering Blog , Tech Radar , and YouTube channel.

What you’ll be doing:

Agentic AI is an increasingly important part of Preply's AI strategy. As a Senior ML Platform Engineer, you'll build the infrastructure that takes agent prototypes to production. You'll solve distributed-systems problems in long-running, non-deterministic workflows that depend on tools, human decisions, and changing context.

This is a hands-on senior role with broad technical influence. You'll write production code, shape platform abstractions and operational standards, and partner with Applied Science, Data, Product, Security and Engineering teams.

In this role, your responsibilities include:

Build a durable agent runtime with checkpoints, retries, timeouts, resumability, and deterministic recovery where possible.

Create a secure tool layer for discovery, registration, invocation and versioning across internal APIs and external services, including MCP where useful.

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.

What you need to succeed:

Proven track record (5+ years) 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 or function calling, structured outputs, and multi-step workflows.