LLM Developer

We are seeking a talented and motivated LLM Developer to join our growing LLM Engineering team. In this role, you will be instrumental in building and enhancing our Large Language Model (LLM) Graph and Agent capabilities. You will work with state-of-the-art LLM technologies, focusing on practical implementation, performance optimization, and robust testing to deliver impactful AI-driven solutions. If you are passionate about pushing the boundaries of what LLMs can do and thrive in a dynamic, innovative environment, we encourage you to apply.

Key responsibilities:

• Develop, implement, and optimize LLM-based applications, with a specific focus on building and improving LLM Graphs and Agents.
• Design and implement robust testing strategies for LLM models and applications, including evaluation metrics, data validation, and adversarial testing.
• Collaborate closely with LLM Engineers and other cross-functional teams to integrate LLM solutions into larger product ecosystems.
• Conduct research and experimentation to identify and evaluate new LLM techniques, libraries, and frameworks.
• Troubleshoot and debug issues related to LLM performance and deployment.
• Stay up-to-date with the latest advancements in the LLM space and proactively share knowledge within the team.
  
  

• 3+ years of professional experience in software development with a strong emphasis on Python.
• Minimum of 1 year of hands-on experience with production LLM usage, including practical application and deployment.
• Demonstrated understanding of LLM testing methodologies, including evaluation metrics, bias detection, and performance benchmarking.
• Experience building and working with LLM frameworks and libraries (e.g., LangChain, LangGraph).
• Strong understanding of data structures, algorithms, and software design principles.
• Experience with version control systems (e.g., Git).
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a collaborative team.
• Take ownership of features
• Fast learner
• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
  
  

• Experience with BigData
• Familiarity with building and deploying AI agents.
• Knowledge of cloud platforms (e.g., GCP) and MLOps practices.
• Experience with containerization technologies (e.g., Docker).
• Understanding of prompt engineering techniques and best practices.
• Experience with other programming languages or frameworks relevant to AI development.