Top Tech Jobs & Startup Jobs in London

Build and operate production infrastructure for reliable agentic AI systems. Responsibilities include durable agent runtimes, secure tool integration, state and memory management, permissions, guardrails, observability, evaluation, SDKs, workflow frameworks, SLOs, and incident response. The role partners across engineering, security, product, data, and applied science while shaping platform architecture and developer experience.

Designs and operates production GenAI platform infrastructure, including model gateways, routing, caching, evaluation, observability, prompt lifecycle management, guardrails, cost controls, and incident response. Partners with engineering, security, privacy, product, data, and applied science teams to create reliable self-service capabilities for AI workloads.

Lead and grow Preply’s Data Platform engineering team, defining the Lakehouse, ingestion, governance, data quality, and reliability strategy. Partner with Analytics, ML, Data Science, Product, Security, and Engineering leaders to prioritize platform investments, guide architecture, improve operational excellence, and deliver trusted data products. Responsibilities include coaching engineers, hiring, setting SLOs, managing incidents, driving execution, and evolving team structure and technical standards.

Own the full product lifecycle for a growth-focused platform area, including product strategy, roadmap development, prioritization, experimentation, metrics, and continuous improvement. Collaborate with engineering, design, and business teams to deliver user-centered features. Use qualitative and quantitative insights to improve learner and tutor experiences, retention, discovery, and business growth.

Manage Preply’s engineering talent acquisition function across global hubs. Lead and coach TA Partners, personally handle complex technical searches, translate workforce plans into hiring strategies, improve recruiting processes, monitor funnel performance, lead interviewer calibration, develop sourcing and talent-mapping strategies, and partner with senior Engineering and TA leaders to deliver high-quality hiring outcomes.

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.

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.

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.