Senior Data Scientist (GenAI)

Quick Facts

• Role: Senior Data Scientist (GenAI)

• Work mode: 100% remote

• Availability: ASAP or within 2 weeks

Description

Build and evolve production-ready GenAI solutions based on LLMs, RAG, and agentic systems. Own the technical approach from concept and experimentation through evaluation and integration with existing systems. Focus on quality, stability, safety/response control, performance, scalability, and cost optimization.

Responsibilities

• Design GenAI solutions aligned with business and technical needs

• Select models and approaches based on specific use cases

• Develop production solutions using LLM, RAG, and agentic systems

• Build mechanisms to use knowledge from multiple data sources

• Design and optimize retrieval, processing, and delivery of context to models

• Create methods to measure quality, stability, and effectiveness of generative solutions

• Experiment with models and adaptation methods for target applications

• Implement controls for model responses and overall solution safety

• Optimize solutions for quality, performance, scalability, and cost

• Design integration of AI components with existing systems and data sources

• Validate new models, frameworks, and approaches for production viability

• Promote technical best practices (design patterns, code quality, GenAI development)

• Co-create standards and reusable components for future AI initiatives

Requirements

• Minimum 6 years of experience in Data Science or AI

• Minimum 2 years of experience with production LLM-based solutions

• Very good Python skills and ability to build quality, testable production code

• Practical experience designing and developing RAG systems

• Very good knowledge of LLMs, agentic systems, and conversational solutions

• Experience with vector search, hybrid search, and reranking; optimize context acquisition

• Practical knowledge of LangChain, LangGraph, or similar GenAI frameworks

• Experience with MCP and integration of models/agents with external tools or data sources

• Very good understanding of LLM evaluation methods and experience measuring generative solution quality

• Very good ML foundations (evaluation methods, metrics, model lifecycle)

• Experience with cloud platforms (Azure/AWS/GCP)

• Knowledge of CI/CD, testing, and containerization of AI solutions

• Ability to translate business problems into technical concepts and solution approaches

• Strong analytical skills for complex AI problems

• Very good English communication skills in an international environment

Benefits

• Work on production projects using LLM, RAG, and agentic systems

• Opportunity to take AI initiatives from concept/experiments to deployment and ongoing optimization

• Flexibility to choose models, technical approaches, and solution strategies for specific problems

• Evaluate new GenAI technologies and apply them in practice

• Help shape project standards and reusable approaches for future AI solutions