Senior Data Scientist - AgenticAI

Securonix is seeking a Senior Data Scientist to design, implement, and operationalize Agentic AI solutions for cybersecurity. The role involves end-to-end ownership of the ML lifecycle, including proof-of-concept development, production deployment, and integration of multi-agent AI systems into security workflows.

Key Responsibilities:

• Operationalize large language models (LLMs) and Agentic workflows (LangChain, LangGraph, LlamaIndex, Crew.AI) for automated security decision-making and threat response.
• Design, deploy, and maintain multi-agent AI systems for log analysis, anomaly detection, and incident response.
• Build proof-of-concept GenAI solutions and evolve them into production-ready components on AWS (Bedrock, SageMaker, Lambda, EKS/ECS) using reusable best practices.
• Implement CI/CD pipelines for model training, validation, and deployment using GitHub Actions, Jenkins, and AWS CodePipeline.
• Manage model versioning with MLflow and DVC, set up automated testing, rollback procedures, and retraining workflows.
• Automate cloud infrastructure provisioning with Terraform.
• Develop REST APIs and microservices containerized with Docker and Kubernetes.
• Monitor models and infrastructure via CloudWatch, Prometheus, and Grafana; optimize performance and cost efficiency.
• Collaborate with data scientists, developers, and security analysts to integrate agentic AI into existing security workflows.

Required Qualifications & Skills:

• Bachelor's or Master's in Computer Science, Data Science, AI, or related field.
• Strong proficiency in Python and production-grade coding for data pipelines and AI workflows.
• Deep MLOps expertise: CI/CD for ML, model monitoring, automated retraining, production-quality best practices.
• Hands-on experience with LLMs, embeddings, vector databases, prompt engineering, and RAG.
• Experience with agentic AI frameworks: LangChain, LangGraph, LlamaIndex, Crew.AI or equivalents.
• Extensive AWS experience: Bedrock, SageMaker, Lambda, EKS/ECS, S3; Athena, Glue, Snowflake preferred.
• Infrastructure as Code using Terraform.
• Building REST APIs and microservices; containerization with Docker and Kubernetes.
• Solid data science fundamentals: feature engineering, model evaluation, data ingestion.
• Understanding of cybersecurity principles, SIEM data, and incident response.
• Excellent communication skills for technical and non-technical audiences.

Preferred Qualifications:

• AWS certifications (Solutions Architect, Developer Associate).
• Experience with Model Context Protocol (MCP) and RAG integrations.
• Familiarity with workflow orchestration tools (Apache Airflow).
• Experience with time series analysis, anomaly detection, and machine learning