Job Description

This is a senior-level, applied AI role for a resourceful and creative engineer who will build, deploy, and refine our consumer-facing AI applications. The successful candidate will lead the development of conversational AI agents and other generative systems that will help redefine how users interact with solutions with AI features. This is a chance to move beyond prototyping to building reliable, production-grade solutions.

Responsibilities:

Lead the development and improvement of the agentic chatbot, including merging different chatbot architectures. Develop intuitive and efficient applications where AI interactions provide value and enhance the user experience. Lead the evaluation of the AI chatbot by creating and running test suites, capturing performance metrics, and comparing results against baseline tools and grounded truths. Enhance chatbot accuracy by implementing new logic (e.g., converting natural language into Cypher queries) and refining prompts. Optimize prompts and manage context for AI interactions by agents and humans. Research and implement solutions to overcome platform limitations and integrate a mix of data sources including vector and graph databases. Intergrade and utilize observability tools like MLflow to monitor, debug, and optimize LLM token usage and Lang Graph calls.

Qualifications:

Bachelor's degree in computer science or software engineering with a thorough understanding of CS fundamentals and theory relevant to application development. Proficient in building agentic systems and multi-tool chatbots using frameworks like LangGraph. Practical experience with AI/LLM development, particularly with chatbots, RAG and agentic systems. Should have worked on Agentic AI frameworks Should have experience in Vector D, Neo4J or similar Graph database Solid Python programming skills and experience with data-intensive applications. Strong background in designing and executing evaluation frameworks for AI and LLM-based systems. Resourceful and proactive approach to technical research and problem-solving. Experience with vector databases and their integration. * Proficiency in the English language.