AI Developer (MCP)

• Applying OCR techniques (e.g., Tesseract, AWS Textract) and LLM-based methods to extract structured and unstructured data.
• Designing and implementing LLM-enhanced workflows, including prompt engineering, RAG pipelines, and retrieval-augmented applications.
• Exploring frameworks such as LangChain, LlamaIndex, or custom orchestration layers for intelligent document comprehension.
• Building and deploying cloud-native services using Docker, AWS ECS, and Lambda, following event-driven architecture principles.
• Ensuring secure and efficient integration of third-party AI/ML services.
• Participating in daily stand-ups, biweekly syncs, and technical interviews.
• Collaborating with distributed teams across Germany and India.
• Contributing to strategic discussions on expanding the solution into broader AI/LLM initiatives, including agent development and model fine-tuning.

• Hands-on Python development experience, with a strong focus on building robust, scalable systems for 5+ years.
• Advanced agentic RAG.
• RAG evaluation hands-on experience.
• Data integration (with or without MCP).
• MCP hands-on experience.
• RAG ecosystems scalability.
• Azure Document Intelligence.
• Hands-on knowledge of document intelligence services, such as AWS Textract and/or Azure Document Intelligence, for OCR and structured data extraction.
• Unstructured.io – for parsing and structuring complex document formats.
• Exposure to GenAI frameworks such as LangChain, LlamaIndex, or custom-built LLM orchestration layers.
• Experience building RAG pipelines or retrieval-enhanced LLM applications.
• Ability to work with cloud-native workflows and integrate third-party ML/AI services securely and efficiently.
• Proven ability to extract content from documents, especially PDF files containing a mix of text and scanned imagery, using both rule-based and ML/LLM-based techniques.
• Practical experience leveraging LLMs for content extraction, including prompt engineering, RAG pipelines, or integrating LLMs into document processing workflows.
• Proficiency in deploying applications using containers (Docker) and orchestrating services with AWS ECS and Lambda, with a good understanding of event-driven architectures.
• Level of English – from Upper-Intermediate and above.

• Experience building RAG pipelines or retrieval-enhanced LLM applications.
• Exposure to GenAI frameworks such as LangChain, LlamaIndex, or custom-built LLM orchestration layers.
• Background in pre-processing and chunking strategies to enhance document comprehension by AI models.
• Prior experience in a GenAI-focused project environment, especially in a consulting, startup, or agile enterprise setting.

• 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.
• English courses.
• Private health insurance and compensation for sports activities.

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