Requirements

Expected technologies

Python

CognigyAI

Databricks

GenAI

NLP

Operating system

Windows

Our requirements

• At least 3 years of commercial experience in Data Science or Machine Learning,
• Expertise in designing, testing, and optimizing solutions for large language models (e.g., ChatGPT, GPT-4).
• Proficiency in Python and at least one AI/data- platform (e.g. CognigyAI, databricks)
• Hands-on expertise with AI/NLP platforms and performance evaluation (A/B testing, error analysis).
• Solid grasp of current AI/ML research, with a focus on best practices for GenAI and emerging agentic AI concepts.
• Strong collaborator in agile, cross-functional teams, with excellent technical communication.
• Awareness of ethical AI practices, including bias mitigation and data privacy.
• Ability to translate complex concepts into accessible language for non-technical stakeholders.
• A systematic approach to identifying issues in existing setup and constructing targeted solutions, including the ability to troubleshoot and optimize model behavior under different conversational scenarios.
• Very good command of English language,
• Proactive attitude and the ability to work as a team player,
• The ability to think beyond the current scope of the project,
• Experience actively participating in a Scrum team by bringing in new solutions,
• Willingness to travel once per quarter,
• Willingness to upskill on your own initiative and deriving further insights from data,
• Willingness to come to our office in Gdańsk two days a week or relocate to Trójmiasto.

Your responsibilities

• Craft and fine-tune advanced LLM prompts to drive high-performance conversational experiences in the Chat Assistant.
• Use a data-driven approach to identify limitations in current conversational models and generate effective solutions for challenges such as user engagement, contextual understanding, and content moderation.
• Design reusable frameworks that encapsulate innovative functionalities and can be adapted across various assistant use cases.
• Collaborate closely with engineering teams to align GenAI strategies with backend enhancements, contributing to architectural optimization and improved task performance.
• Prototype, deploy and maintain new LLM or agentic AI based strategies to support emerging features and expand the assistant’s capabilities.
• Continuously evolve the LHG Chat Assistant architecture with a focus on deepening the assistant’s natural language understanding and response relevance, integrating agentic AI principles to enable more adaptive, goal-oriented interactions in our redesigned system.
• Build LLM-backed transactional flows.
• Transition towards agentic AI, orchestrate hybrid solution with AI + deterministic logic.
• Implement and maintain function calling to backend systems or APIs.
• Automated testing for all components of AI solutions (prompt, flows, function calls, etc.).