Jobs at Preply

Owns risk, reputation, and crisis communications across Preply. Responsibilities include identifying emerging issues, developing response strategies and messaging, maintaining crisis frameworks and playbooks, monitoring media and online conversations, coordinating sensitive media inquiries, preparing spokespeople, leading simulations, advising senior leaders, and partnering cross-functionally with Legal, Trust & Safety, Product, People, and other teams.

Lead GenAI and Agentic Platform engineering across two teams of approximately 8–12 engineers. Set technical strategy, guide architecture for model access, evaluation, observability, retrieval, orchestration, tools, memory, permissions, and safety, and partner with Product, Applied Science, Data, Security, and Engineering. Responsibilities include hiring, coaching, organizational health, platform prioritization, stakeholder alignment, build-versus-buy decisions, and delivering reliable, scalable AI infrastructure.

Build and operate backend services, internal developer platforms, CI/CD systems, testing capabilities, and developer tooling using Python. Improve developer productivity and experience through scalable paved paths, cloud-native systems, distributed architectures, and AI-native development workflows. Partner with engineering teams to identify friction, measure platform effectiveness, and enable autonomous software delivery.

Productionize and operate reliable machine learning systems across training, evaluation, deployment, monitoring, and LLM feature delivery. Build scalable batch and streaming data pipelines, containerized training environments, cloud infrastructure, feature transformations, and observability systems. Develop internal Python tooling, manage compute resources, ensure reproducibility and testing, and collaborate with ML scientists, backend engineers, and data engineers. Mentor peers and support secure, modular ML services throughout the model lifecycle.

Own end-to-end recruitment for complex, senior, and niche engineering searches. Partner with senior engineering leaders, develop active sourcing strategies, analyze recruiting funnel metrics, support calibration and interview training, improve hiring processes, coach recruiting peers, and deliver an exceptional candidate experience.

Build AI agents, reusable agent capabilities, and agentic workflows that automate software development at Preply. Develop integrations with codebases, APIs, MCPs, internal tools, and engineering systems; design orchestration, context, evaluation, verification, and human-in-the-loop mechanisms; and take prototypes into reliable, scalable solutions. Collaborate across engineering, product, design, and data teams while measuring adoption and business value.

Lead Preply’s global IT function, setting strategy while remaining hands-on with identity, endpoint management, automation, and scripting. Manage international device lifecycle, workplace technology, SaaS spend, vendor relationships, IT security controls, dashboards, and compliance readiness. Develop a high-performing team, introduce AI-native operations, partner with Security and Finance, and advise C-level stakeholders on technology, cost, risk, and employee experience.

Own the strategy, roadmap, and launch of Preply’s new non-language-subjects vertical. Lead a 0-to-1 product initiative spanning tutor and learner experiences, partnering with design, research, data science, engineering, marketing, and supply teams. Prioritize opportunities, validate decisions through experiments and research, define success metrics, and influence leadership while scaling a new marketplace business.

Own the strategy, roadmap, OKRs, and adoption of internal platform capabilities that improve developer productivity, reliability, delivery speed, and cost efficiency. Identify engineering pain points, define product requirements, evaluate technical trade-offs, establish standards, and lead migrations and deprecations. Partner closely with engineering managers and senior engineers while using developer experience research, incident reviews, DORA metrics, SLOs, and platform data to guide decisions.

Lead the development of AI-powered personalized learning solutions, including deep learning, NLP, information retrieval, LLM, and multimodal systems. Shape Preply’s scientific roadmap, advise senior leadership, partner with product and engineering teams, mentor scientists and engineers, and establish machine learning architecture, research, and deployment best practices. The role spans research through production and focuses on scalable solutions for personalized learning and intelligent tutor systems.

Own data strategy and experimentation for a critical product domain, influencing senior leadership decisions through causal inference, forecasting, LTV modeling, retention analysis, pricing analysis, and scenario planning. Define key metrics, lead strategic analytical initiatives, improve measurement frameworks, and mentor senior data scientists while partnering with Product, Engineering, and Business leaders.

Own and scale Preply’s revenue operations systems, architecture, automation, data governance, reporting, and tooling strategy. Lead Salesforce and connected GTM platforms, improve lead-to-renewal workflows, build dashboards, manage vendors and budgets, and deliver insights for forecasting and growth decisions. Lead a small team while partnering across Sales, Marketing, Customer Success, Finance, Product, and Enablement to implement scalable processes and improve adoption, accuracy, and efficiency.

Lead technical strategy and architecture for Learning Teams, drive end-to-end strategic initiatives, evolve core services for scalability and reliability, improve engineering practices and developer experience, mentor senior engineers, and make build-vs-buy and tooling decisions.

Lead design and evolution of core analytical data models, define analytics engineering standards, build and optimize ETL/ELT pipelines, own the BI/semantic layer (Looker/LookML), drive data quality and governance, partner with cross-functional teams, and mentor analytics engineering across the company to enable reliable, scalable decision-making and experimentation.

The role involves owning operational processes for the Data & Applied AI team, ensuring alignment, tracking project delivery, and improving team efficiencies while working closely with the VP.

Leads and develops high-performing engineering teams responsible for learner growth or monetization products. Sets technical and product strategy, drives execution, coaches engineers, guides architecture and technical trade-offs, and promotes engineering best practices, reliability, quality, and continuous improvement. Partners with Product, Data, and Design to prioritize high-impact initiatives and deliver measurable customer and business outcomes.

Lead platform security across cloud and Kubernetes environments, build detection and response capabilities, improve logging and identity access controls, drive cross-functional security initiatives, create runbooks and playbooks, participate in on-call rotations, and automate secure patterns across CI/CD and infrastructure.

Lead recruitment marketing activations to attract engineering, data/AI, design and commercial talent. Plan and execute events, campaigns, Glassdoor strategy, careers page improvements, and paid/organic recruitment channels. Measure impact and partner with TA, Brand, and stakeholders to turn attraction into qualified hiring pipelines.

Lead design and roadmap for a scalable ML/GenAI platform: lifecycle architecture (training, deployment, monitoring), cloud-native GPU infrastructure, CI/CD for ML, observability and governance, LLM/vector retrieval capabilities, self-service tooling, cross-functional alignment, and mentoring senior engineers to accelerate safe, cost-efficient production ML at company scale.

Lead FP&A for B2C marketing economics: own modeling, forecasting, scenario analysis, and executive reporting. Partner with Growth Marketing on channel investment, geo expansion, incrementality, and paid/organic dynamics. Build investment frameworks, guardrails, and ROI-driven decision tools using Looker, Excel/Sheets and AI to improve model accuracy and inform CMO/CFO-level decisions.