Senior Data Scientist - Agentic AI & MLOps

Role Summary:

Architect and operationalize Agentic AI solutions, managing the full ML lifecycle from proof-of-concept to production. Build multi-agent AI systems for cybersecurity tasks, implement MLOps best practices, and integrate AI workflows into security operations.

Key Responsibilities:

• Operationalize large language models and Agentic workflows to automate threat response
• Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response
• Build GenAI proof-of-concepts and production-ready components on AWS using Bedrock, SageMaker, Lambda, EKS/ECS
• Implement CI/CD pipelines for ML with GitHub Actions, Jenkins, and AWS CodePipeline
• Manage model versioning, automated testing, rollback procedures, and retraining workflows
• Automate cloud infrastructure with Terraform, build REST APIs, and containerize microservices with Docker and Kubernetes

Minimum Requirements:

• Bachelor's or Master's in Computer Science, Data Science, AI, or related discipline
• 4+ years of software development, 3+ years in LLM-based/Agentic AI architectures
• Strong knowledge of generative AI fundamentals, embeddings, vector databases, prompt engineering, and RAG
• Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI, or equivalent frameworks
• Python proficiency and production-grade coding for data pipelines and AI workflows
• Deep MLOps knowledge including CI/CD for ML, model monitoring, automated retraining, and production-quality best practices
• Extensive AWS experience, Terraform, Docker, Kubernetes, and REST API development
• Understanding of cybersecurity principles, SIEM data, and incident response