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

Senior Data Scientist - AgenticAI