AI Platform Engineer in the EU
Andersen Lab
Andersen is hiring an AI Platform Engineer in the EU for a project developing a next-generation AI platform and delivering scalable intelligent solutions powered by LLMs and AI technologies.
The customer is an organization that provides education and professional development services with a focus on practical, skills-oriented learning. It combines academic and applied approaches to help learners develop competencies relevant to evolving professional environments. The organization collaborates with external partners to enrich learning experiences through practical projects, knowledge exchange, and real-world applications. It also promotes innovation, continuous learning, and career readiness by fostering an engaging and supportive educational environment.
The project is focused on developing a next-generation AI platform for sports organizations. It leverages LLMs, AI agents, and Retrieval-Augmented Generation (RAG) to build intelligent workflows, extend AI platform capabilities, and deliver scalable, enterprise-grade AI solutions.
Responsibilities:
Designing and building AI agent workflows on Dify.
Extending Dify with custom components and integrations.
Building custom tools, APIs, and backend integrations.
Designing agent orchestration and system behavior.
Defining prompting, tool usage, and structured outputs.
Designing end-to-end RAG architectures.
Building document ingestion and indexing pipelines.
Optimizing chunking, metadata, and embeddings.
Designing retrieval, reranking, and grounding strategies.
Improving citation quality and response accuracy.
Optimizing latency, context usage, and token efficiency.
Building automated AI evaluation pipelines.
Defining quality metrics and benchmark datasets.
Debuging retrieval, prompting, and agent behavior.
Measuring quality, latency, and cost.
Defining human review workflows where needed.
Working closely with Product and Engineering.
Collaborating on backend architecture and APIs.
Documenting platform architecture and designing decisions.
Must-haves:
Experience in Data Engineering, 4+ years.
Strong Python and/or TypeScript skills.
Experience building production LLM applications.
Experience with Dify or similar AI frameworks.
Experience extending AI frameworks beyond configuration.
Strong experience building RAG systems.
Strong understanding of embeddings, vector search, chunking, reranking, and grounding.
Experience integrating LLMs with APIs and business systems.
Experience evaluating AI quality and reliability.
Ability to debug complex AI workflows.
Strong engineering mindset and pragmatic problem-solving.
Excellent communication and documentation skills.
Level of English - from Intermediate+ and above.
Nice-to-haves:
Experience extending Dify at source-code level.
Experience with LangGraph, LangChain, LlamaIndex, Haystack, or similar frameworks.
Experience with vector databases such as Qdrant, Weaviate, Pinecone, OpenSearch.
Experience with OpenAI, Anthropic, Azure OpenAI, Mistral, or open-source models.
Experience with AI observability and evaluation platforms.
Experience with function calling, structured outputs, and MCP.
Experience building enterprise AI applications.
Experience with security-conscious or regulated environments.
Reasons why this job would be interesting to you:
Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others. Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc.;
The opportunity to change the project and/or develop expertise in an interesting business domain;
Job conditions - you can work both fully remotely and from the office or can choose a hybrid variant;
Guarantee of professional, financial, and career growth! The company has introduced systems of mentoring and adaptation for each new employee;
The opportunity to earn additional up to 1,000 USD per month by participating in the company's activities;
Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated;
Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies);
Certification compensation (AWS, PMP, etc);
Referral program;
Private health insurance and compensation for sports activities.
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