Building customer-facing and internal-facing intelligent chatbots and workflows that push the boundaries of agentic technology.
Requirements
- Strong proficiency in Python and Go, with proven experience in agentic frameworks
- Hands-on experience with Retrieval-Augmented Generation (RAG) and vector database technologies
- Knowledge of Agentic frameworks like LangChain and LangGraph for orchestrating AI workflows
- Solid grasp of machine learning and natural language processing (NLP) principles
- Strong understanding of data modeling and data architecture
- Familiarity with data quality checks and validation processes
- Experience with streaming speech-to-text and text-to-speech technologies
Responsibilities
- Develop and implement AI agentic applications using Python and Go, leveraging modern agentic frameworks
- Build and optimize Retrieval-Augmented Generation (RAG) systems for enhanced AI performance
- Design and manage vector databases (e.g., pgvector, FAISS) for efficient data handling
- Utilize agentic frameworks to create robust workflows for language models and agent coordination
- Conduct evaluation of models to assess performance, accuracy, and reliability, iterating as needed
- Perform prompt engineering and tuning to optimize large language model outputs for specific use cases
- Debug, troubleshoot, and enhance AI systems for scalability and reliability
Other
- Degree in Computer Science, Engineering, or a related field or equivalent experience
- Exceptional problem-solving skills and meticulous attention to detail
- Collaborate with team members to define requirements and deliver production-ready solutions
