Job
Description
At Securonix, we re on a mission to secure the world by staying ahead of cyber threats, reinforcing all layers of our platform with AI capabilities. Our Securonix Unified Defense SIEM provides organizations with the first and only AI-Reinforced solution built with a cybersecurity mesh architecture on a highly scalable data cloud. Enhanced by Securonix EON s AI capabilities, our innovative cloud-native solution delivers a seamless CyberOps experience, empowering organizations to scale their security operations and keep up with evolving threats. Recognized as a five-time leader in the Gartner Magic Quadrant for SIEM and highly rated on Gartner Peer Insights , our award-winning Unified Defense SIEM provides organizations with 365 days of hot data for rapid search and investigation, threat content-as-a-service, proactive defense through continuous peer and partner collaboration, and a fully integrated Threat Detection, Investigation, and Response (TDIR) experience all within a single platform. Built on a cloud-native architecture, the platform leverages the Snowflake Data Cloud for unparalleled scalability and performance. Securonix is proud to be a cybersecurity unicorn and featured in CRNs 2024 Security 100 list. Backed by Vista Equity Partners , one of the largest private equity firms with over $100 billion in assets under management, we have a unique advantage in driving innovation and growth. With a global footprint, we serve more than 1,000 customers worldwide , including 10% of the Fortune 100. Our network of 150+ partners and Managed Security Service Providers (MSSPs) enables us to deliver unmatched security solutions on a global scale. At Securonix, we are driven by our core values and place our people at the heart of everything we do: Winning as One Team: We work together with universal respect to achieve aligned outcomes Customer Driven Innovation: We innovate to stay ahead of the market and create value for our customers Agility in Action: We embrace change and are unified in our purpose and objectives amidst change Join us as we redefine cybersecurity, innovate fearlessly, and grow together as one team. About Us: Securonix delivers next-generation security analytics and operations management. We secure organizations worldwide by staying ahead of cyber threats, leveraging AI-reinforced capabilities for unparalleled protection. Job Overview: We re seeking a Senior Data Scientist to architect Agentic AI solutions and own the full ML lifecycle from proof-of-concept to production. You ll operationalize LLMs, build Agentic workflows, implement MLOps best practices, and design multi-agent systems for cybersecurity tasks. Key Responsibilities: Operationalize large language models and Agentic workflows (LangChain, LangGraph, LlamaIndex, Crew.AI) to automate 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 with 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 and develop REST APIs and microservices containerized with Docker and Kubernetes. Monitor models and infrastructure through CloudWatch, Prometheus, and Grafana; analyze performance and optimize for cost and SLA compliance. Collaborate with data scientists, application developers, and security analysts to integrate agentic AI into existing security workflows. Qualifications: Bachelor s or Master s in Computer Science, Data Science, AI or related quantitative discipline. 4+ years of software development experience, including 3+ years building and deploying LLM-based/agentic AI architectures. In-depth knowledge of generative AI fundamentals (LLMs, embeddings, vector databases, prompt engineering, RAG). Hands-on experience with LangChain, LangGraph, LlamaIndex, Crew.AI or equivalent agentic frameworks. Strong proficiency in Python and production-grade coding for data pipelines and AI workflows. Deep MLOps knowledge: CI/CD for ML, model monitoring, automated retraining, and production-quality best practices. Extensive AWS experience with Bedrock, SageMaker, Lambda, EKS/ECS, S3 (Athena, Glue, Snowflake preferred). Infrastructure as Code skills with Terraform. Experience building REST APIs, microservices, and 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 both 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.
