Description

Design, build, and deploy AI-powered agents and knowledge graphs to optimize enterprise business processes.

You will own the release pipeline for AI models, ensuring reliable deployment and monitoring.

Responsibilities

• Design and deploy AI agents for task automation and virtual assistants using LLMs.
• Develop knowledge graphs for enterprise data integration and structured retrieval.
• Implement AI/ML CI/CD pipelines to automate model deployment and integration.
• Establish real-time monitoring for model performance, drift detection, and accuracy.
• Build automated retraining pipelines to maintain model accuracy against shifting data patterns.

Required Skills

• 5+ years of experience in AI engineering and MLOps practices.
• Proficiency in Python or Java.
• Hands-on experience with Large Language Models (LLMs) including GPT-3/4, GPT-J, or BLOOM.
• Experience with knowledge graph technologies, ontology design, and graph databases like Neo4j.
• Expertise in AI Ops/MLOps, including CI/CD pipelines and model lifecycle management.
• Experience using Azure Machine Learning Studio or Google Vertex AI.
• Practical knowledge of MLflow, Kubeflow, Docker, and Kubernetes.
• Strong foundation in Natural Language Processing (NLP) and conversational AI.
• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.

Preferred Skills

• Experience building conversational AI agents using Microsoft Bot Framework or Rasa.

Key Skills

Education

Bachelor's or Master's degrees