Senior ML Platform Engineer (GenAI Platform)

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.

The GenAI Platform team sits within Platform Engineering. We build the shared infrastructure that helps product teams develop, evaluate, deploy and operate GenAI safely at scale. Our scope includes the GenAI gateway, model and prompt lifecycle, evaluation, observability, cost controls and guardrails.

We work closely with ML Platform, which supports core machine learning workflows, and Agentic Platform, which provides agent orchestration, state management and tool integration. Together, we give product teams a consistent foundation for user-facing AI experiences and autonomous agents.

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:

GenAI is central to Preply's product strategy. As a Senior ML Platform Engineer, you'll design and build the systems behind production GenAI workloads. You will drive the expansion of our GenAI Platform, and turn recurring engineering needs into reliable self-service capabilities.

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:

• Architect unified gateway with automated routing, quota controls, and resilient fallback systems across model vendors.
• Drive system efficiency and low latency via dynamic traffic management, response caching, token budgeting, and cost allocation controls.
• Establish robust evaluation mechanisms to guarantee high precision, stability, and safety in model outputs.
• Deliver system observability, providing deep tracing, performance telemetry, cost analytics, continuous monitoring, and alerting across GenAI lifecycles.
• Standardize prompt engineering workflows with automated versioning, automated testing, governance, and CI/CD integrations for production delivery.
• Embed platform guardrails alongside Security and Privacy experts to enforce policies, and safe production defaults automatically.
• Maintain sustainable incident response, blameless postmortems, and comprehensive monitoring for GenAI stacks.

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
• Practical experience with GenAI systems, including vector retrieval, external provider APIs, and common issues.
• AI Expertise: You're a forefront user of Agentic AI. You're able to bring hands-on experience and start influencing the team beyond code generation; reserving judgment for architecture, business logic, and security, using AI as a thought partner and being able to set up quality gates and safety nets to enhance existing engineering workflows and propose AI-native alternatives.
• Sound knowledge of distributed systems, including high availability, concurrency, caching and rate limiting.
• Experience with at least one major public cloud, its services and infrastructure (preferably AWS).
• Hands-on experience with distributed tracing, system telemetry, SLOs, and incident triage.
• Strong communication skills and at least C1 English level, plus willingness to join a paid on-call rotation.

Nice to have:

• Experience operating AI gateways or scalable model serving infrastructure.
• Familiarity with evaluation suites, prompt management, vector databases, or customized GenAI observability tooling.
• Experience with Metaflow, Databricks, or AWS SageMaker.
• Knowledge of hosting open-source foundation models, optimizing GPU compute, dynamic scaling, and infrastructure cost controls.
• Familiarity with agentic workflows, multi-agent frameworks and tool-use patterns.

Why you’ll love it at Preply:

• Open, collaborative, dynamic, and diverse culture.
• Generous monthly allowance for lessons on Preply.com .
• Learning & Development budget, including time off for your self-development.
• Competitive financial package with equity and leave allowance.
• Opportunity to shape the lives of learners and tutors from over 175 countries through language learning and teaching.