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.
- Robust 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

Skills: Docker, Kubernetes, Terraform, Lambda, Python

Experience: 3.00-7.00 Years

📌 Senior Data Scientist - AgenticAI (Bengaluru)
🏢 Securonix Consultancy
📍 Bengaluru