NEWPosted 3 hours ago

Job ID: JOB_ID_5963

Role Overview:

This role is critical for designing, developing, and optimizing the core AI and RAG components of the system. The ideal candidate will have a deep understanding of generative AI models, LLMs, and their application in conversational interfaces, with expertise in building agentic systems using LangGraph.

Key Skills & Responsibilities:

  • Gen AI: Deep understanding of generative AI models, LLMs, and their application in conversational interfaces. Experience with fine-tuning or adapting models for specific tasks.
  • LangGraph: Expertise in building agentic systems and state machines using LangGraph. Understanding of agent orchestration, managing conversational flow, and integrating various tools/models.
  • Python: Strong proficiency in Python, including experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face).
  • RAG Implementation: Experience in designing and implementing Retrieval Augmented Generation systems, including vector databases, embedding techniques, and efficient retrieval strategies.
  • Cloud Platform (Google Cloud): Experience deploying and managing AI/ML workloads on Google Cloud Platform (GCP) is an added advantage. Familiarity with relevant services like Vertex AI, Cloud Functions, Cloud Run, or GKE for model deployment.
  • Async Programming: Understanding or ability to write efficient asynchronous code for handling potentially long-running AI model calls and external API interactions.
  • REST: Understanding of RESTful principles for integrating AI services with other parts of the system.
  • Logging: Experience with implementing robust logging for monitoring AI model performance, identifying issues, and tracking usage. Familiarity with tools like Splunk is a plus.

Compensation & Location

Salary: $100,000 – $150,000 per year (Estimated)

Location: Charlotte, NC

Recruiter / Company – Contact Information

Email: inthlobovysystems@gmail.com

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