Live opening · Posted 2 days ago
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About the role
Description supplied by the original job listing.
Responsibilities:
Develop, test, and deploy backend automation systems that enhance SOC workflows using cloud-native, data-intensive, and AI-driven architectures.
Design, develop, and maintain backend services and microservices using Python, Go, and scalable cloud-native patterns.
Build secure, high-availability systems leveraging AWS services, including RDS, DynamoDB, Lambda, and Kubernetes/EKS.
Build and maintain detection pipelines, incident response playbooks, enrichment services, and agentic automation systems.
Integrate software components into robust, production-ready systems with strong observability, documentation, and maintainability.
Collaborate closely with threat detection, incident response, data science, and platform engineering teams to deliver secure, reliable, and context-aware automation capabilities.
Apply test-driven development and CI/CD practices using Git, Jenkins, Terraform, Docker, and infrastructure-as-code workflows.
Contribute to architectural discussions on integrating LLMs, reasoning agents, and autonomous task execution frameworks into SOC tooling.
Solve complex problems creatively using advanced analytical and debugging techniques across distributed systems.
Explore and prototype innovative uses of AI in detection, triage, automation, and response workflows.
Mentor junior developers and contribute to team growth through knowledge sharing and technical leadership.
Requirements:
9+ years of experience in backend software development, infrastructure engineering, or security-focused systems.
Strong understanding of automation design patterns, distributed systems, and cloud-native application design.
Experience building large-scale, production-grade backend systems using Python, Go, or similar languages.
Familiarity with AWS (preferred), GCP, or Azure, along with strong knowledge of CI/CD pipelines and DevOps tooling.
Hands-on experience with Kubernetes, Docker, Terraform, and microservices architectures.
Experience integrating or building systems with AI/ML components and automation in production environments.
Strong understanding of data pipelines, streaming systems, or detection workflows.
Proven ability to work independently on large features and contribute to architectural decisions.
Strong problem-solving mindset with the ability to translate SOC and security goals into scalable technical solutions.
Passion for working in fast-moving, mission-driven environments where security, AI, and engineering excellence meet.
Experience
8-12 yrs
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