Role Overview
We are looking for a highly skilled LLM Engineer to design and develop a GenAI-based solution for automating the migration of RPA BOTs from UiPath/Automation Anywhere to ServiceNow RPA. The ideal candidate will be responsible for fine-tuning large language models (LLMs) and creating a system capable of interpreting and converting source XML files into ServiceNow RPA-compatible XML files. This role requires a strong understanding of LLM algorithms, RPA systems, and automation workflows.
Key Responsibilities
- Research, select, and fine-tune appropriate LLM algorithms to support XML-to-XML conversion for RPA migration.
- Develop and train LLMs using curated training data provided by the RPA development team.
- Design a robust pipeline for parsing source XML files and generating ServiceNow RPA-compatible XML outputs.
- Incorporate validation mechanisms within the LLM to ensure the correctness of converted BOTs.
- Work closely with RPA developers to iterate on feedback loops and improve the model's accuracy and reliability.
- Develop a mechanism for validating the LLM-converted BOTs and generating corrective feedback for further refinement.
- Optimize the solution for scalability and maintainability in enterprise environments.
- Document processes, methodologies, and performance metrics to ensure traceability and knowledge transfer.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Strong experience in building and fine-tuning LLMs using frameworks like HuggingFace.
- Familiarity with parsing and processing XML files programmatically.
- Proficiency in Python or other programming languages relevant for machine learning and data manipulation.
- Strong problem-solving skills with the ability to work in cross-functional teams.
- Excellent communication and documentation skills.
Preferred Skills
- Experience with RPA platforms like UiPath, Automation Anywhere, or ServiceNow RPA is a plus.
- Knowledge of ServiceNow RPA architecture and components.
- Hands-on experience in building automated conversion tools.
- Familiarity with version control systems like Git and DevOps workflows.
- Knowledge of prompt engineering and retrieval-augmented generation (RAG) techniques.