Staff Data Scientist

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 CRN's 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 Staff 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.

**Qualifications**:

- Bachelor’s or Master’s in Computer Science, Data Science, AI or related quantitative discipline.
- 8+ 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 (Solution