Description
You will design, build, and deploy AI-powered agents and implement knowledge graphs to optimize enterprise business processes.
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.