AI Engineer (NLP, RAG)

- 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).

- 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.

- Experience collaborating with leaders in FinTech, Healthcare, Retail, and Telecom, including companies like Samsung, Siemens, and Johnson & Johnson.
- Opportunities to switch projects and develop expertise in various business domains.
- Flexible work conditions: fully remote, office-based, or hybrid options available.
- Professional, financial, and career growth guaranteed, with mentoring and adaptation systems for new employees.
- Potential to earn an additional $1,000 per month through company activities, included in the annual bonus.
- Access to a constantly updated corporate training portal with a comprehensive knowledge base.
- Engaging corporate culture with events like parties, game days, and snacks.
- Compensation for certifications (AWS, PMP, etc.).
- Referral program.
- Private health insurance and sports activity compensation.Join us!

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