AI Engineer

Remote.AR
Remote.Brazil
Remote.Bulgaria
Remote.Colombia
Remote.Georgia
Remote.Kazakhstan
Remote.Poland
Rosario
Алмати
Астана
Белград
Варна
Варшава
Вроцлав
Днепър
Ереван
Киев
Клуж-Напока
Краков
Ларнака
Лвов
Лодз
Люблин
Монтевидео
Монтерей
Одеса
Рига
София
Тбилиси
Харков

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Client

A world-renowned higher education institution based in London, recognized as a leader in global business education. The organization is currently expanding its dedicated AI Lab to drive digital transformation and innovation across its academic and administrative functions.

Project overview

The AI Lab operates as an experimentation-first environment focused on rapidly developing, validating, and shipping AI-powered solutions. The project involves building greenfield AI agents and RAG-based tools for up to 2,000 internal users, as well as scaling an existing course recommendation engine through deep database integration and pipeline optimization.

Position overview

We are seeking a hands-on AI Engineer to serve as the primary technical contributor within a fast-moving, low-overhead setup. You will be responsible for the full lifecycle of AI development - from data validation and backend Python engineering to lightweight frontend prototyping and Azure-based deployment. This role requires a "multiple hats" approach, balancing rapid MVP development with the rigors of production-grade observability and data compliance.

Responsibilities

AI Development & Iteration: Design and build AI agents (OpenAI, Anthropic) and RAG architectures; lead hypothesis-driven development cycles to move from MVP to production based on stakeholder feedback.
System Extension: Enhance an existing course recommendation agent by integrating internal databases and improving underlying data pipelines for better coverage and quality.
Observability & Debugging: Instrument AI flows using LangFuse to monitor agent behavior, conduct prompt evaluations, and resolve latency or logic issues.
Data Validation: Critically assess stakeholder datasets for reliability and GDPR compliance; communicate technical limitations of data to non-technical partners.
UI Prototyping: Build functional, lightweight frontends using AI-assisted workflows (e.g., Lovable, Figma) to surface tools to end-users.
Infrastructure Management: Deploy and maintain solutions within a pre-configured Azure environment, utilizing CI/CD pipelines and following established environment management practices.
Stakeholder Engagement: Collaborate directly with product and academic stakeholders to translate loosely defined needs into technical requirements and buildable solutions.

Requirements

4+ years of experience in backend or full-stack development with a focus on production AI/ML systems using Python.
Proven track record building AI agents and deploying RAG architectures using OpenAI or Anthropic APIs.
Experience with LangFuse or similar tracing tools for LLM pipeline monitoring and prompt engineering.
Hands-on experience deploying solutions on Microsoft Azure (Azure OpenAI, App Services) and familiarity with CI/CD and Terraform.
Ability to analyze and critique datasets and forecast infrastructure/API run costs.
Solid understanding of GDPR and data privacy within an enterprise or institutional context.
Ability to operate as a solo technical lead and explain complex trade-offs to non-technical stakeholders.

Nice to have

Experience within the EdTech or higher education sector.
Background in consultancy or client-facing technical roles.
Specific experience with recommendation systems or personalization engines.
Exposure to "lab-style" or hypothesis-driven product development environments.

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AI Engineer

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Project overview

Position overview

Responsibilities

Requirements

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