Senior Software Engineer - Back-End & Agentic AI

Job description

Securonix is leading the transformation of cybersecurity by helping organizations stay ahead of modern threats. Security teams are no longer constrained by data or tools. They are constrained by speed, clarity, and confidence. Securonix was built to close that gap. Our mission is to enable security teams to decide and act faster across the entire threat lifecycle. The Securonix Unified Defense SIEM is the industry’s first platform powered by agentic AI and designed with a human-in-the-loop philosophy. It unifies detection, investigation, and response in a single system. Advanced UEBA delivers deep behavioral insight across users, entities, and data. Native threat intelligence continuously enriches detections and investigations with real-world context. AI reinforces every layer of the platform while keeping accountability with the security team. Securonix is recognized as a six-time Leader in the Gartner Magic Quadrant for SIEM and a Customers’ Choice on Gartner Peer Insights. The company has been featured by leading publications including WIRED, Dark Reading, and Fortune for its innovation and leadership in security operations. Organizations rely on the platform for always-available data, rapid search and investigation, continuously updated threat content, and a fully integrated Threat Detection, Investigation, and Response experience. Responsibilities: Design, develop, and maintain our industry leading Threat Intelligence Platform – ThreatQ , with a focus on performance, scalability, and maintainability Collaborate with team members, product owners, and designers to implement product requirements Participate in code reviews, providing and receiving constructive feedback to maintain code quality standards Oversee and mentor a team of software developers, providing technical guidance and fostering a culture of continuous improvement. Collaborate with product managers, security analysts, and other stakeholders to understand requirements and translate them into technical specifications. Develop and maintain high-quality code, ensuring adherence to best practices and coding standards. Stay current with emerging technologies and industry trends in cybersecurity, integrating new tools and techniques into development processes as appropriate . Contribute to the development of technical documentation, including design specifications, user guides, and API documentation. Required Skills: A minimum of 6 - 8 years of experience with a bachelor’s degree in computer science or related field. Strong hands-on experience in PHP (Laravel) and/or Python, and object-oriented programming principles Experience with SQL and database systems, such as MariaDB, MongoDB, Redis, and Solr Experience with front-end technologies, such as React, JavaScript, HTML, TypeScript and CSS Solid understanding of CI /CD development lifecycle. Hands-o n experience with GIT version control ( GitHub /Bitbucket/GitLab). Experience with RabbitMQ or similar message queue/async job systems Familiarity with RESTful APIs and JSON Experience with testing frameworks and libraries, such as PHPUnit , pytest , or Jest Knowledge of microservices architecture and containerization technologies, such as Docker or Kubernetes Experience with AWS and Infrastructure-as-Code (Terraform); familiarity with on-prem Kubernetes (RKE2) a plus Experience working in Agile development environments AI Tools & Agent Integration Experience: Experience using AI-powered developer tools (e.g., coding assistants, internal copilots, workflow automation) to improve engineering productivity, code quality, and development efficiency. Experience designing, prototyping, and integrating AI agents and intelligent services into internal systems and customer-facing products. Experience collaborating with product, security, and platform teams to incorporate AI capabilities that meet enterprise requirements for reliability, security, and scalability. Experience mentoring or guiding engineers on effective use of AI tools, prompt engineering techniques, and practical evaluation of AI-driven features in production environments. Nice to Have: Experience designing multi-environment Terraform/Helm deployments spanning cloud (AWS EKS) and on-prem Kubernetes (RKE2) targets. Experience in scaling SaaS environments Experience with event-driven/queue-based architecture (e.g., RabbitMQ, Event Sourcing, Event Listeners)