TELECOMMUTE AI Engineer

• Building hierarchical and multi-agent RAG systems with robust orchestration layers (LangChain, LangGraph; LlamaIndex is a plus).

• Ensuring the scalability and reliability of RAG ecosystems across diverse data sources.

• Applying advanced retrieval techniques - semantic chunking, late/latent chunking, re-ranking models.

• Defining and monitoring evaluation metrics to continuously improve retrieval quality and response accuracy.

• Implementing ingestion and parsing workflows using Unstructured.io, Pydantic, and custom ETL pipelines.

• Building and deploying services with Docker, AWS ECS, and Lambda, following event-driven architecture principles.

• Integrating third-party AI/ML services securely and efficiently.

• Participating in daily stand-ups, biweekly syncs, and technical interviews.

• Collaborating with distributed teams across multiple time zones.

• Contributing to strategic discussions on expanding the solution (agent development, model fine-tuning, new LLM use cases)., * 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 up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, 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.

• Hands-on AI/ML engineering for 5+ years, with strong production Python and a focus on building robust, scalable systems.

• Proven experience with advanced agentic RAG - hierarchical and/or multi-agent architectures.

• Hands-on RAG evaluation experience: defining and monitoring metrics to improve retrieval and response quality.

• Experience with advanced retrieval and pre-processing/chunking strategies (semantic chunking, late/latent chunking, re-ranking).

• Experience with GenAI orchestration frameworks (LangChain, LangGraph, or custom LLM orchestration layers).

• Hands-on with document intelligence / OCR services: AWS Textract and/or Azure Document Intelligence, plus Unstructured.io for parsing complex formats.

• MCP hands-on experience (or strong working knowledge and the ability to implement it).

• Data integration experience (with or without MCP); secure, efficient integration of third-party ML/AI services.

• Experience with cloud-native development on AWS: Docker, AWS ECS, Lambda.

• Solid understanding of event-driven architecture.

• Proficiency in Python and Pydantic, with strong knowledge of data pipelines and modular service design.

• Experience scaling RAG ecosystems across diverse data sources.

• Level of English - from Upper-Intermediate and above.

Nice to have:

• Experience with LlamaIndex and other GenAI orchestration tooling.

• Experience with Vision-Language Models (VLMs) for scanned-document/image understanding, and experience handling multilingual / encoding challenges in OCR.

• Model fine-tuning and domain-adaptation experience.

• Familiarity with AWS Bedrock (Claude/Sonnet) and Azure embeddings.

• Exposure to Google Cloud Platform Vertex AI.

• Advanced degree (MSc/PhD) in a relevant field, or research/publications in AI (CV/NLP).

Andersen is hiring an AI Engineer (NLP, RAG) in the EU for a project developing GenAI solutions, intelligent automation, and AI-powered knowledge management systems.

The customer is a global technology organization delivering digital products and business solutions to customers across multiple industries and markets. The company focuses on helping organizations improve operational effectiveness, optimize processes, and support business growth through the use of modern technologies, data-driven approaches, and scalable platforms. The project is focused on developing AI-powered solutions that support digital transformation through intelligent document processing, knowledge retrieval, and automation. It includes building and enhancing production-grade GenAI applications that improve operational efficiency, decision-making, and access to critical information.