About the Role: Cloud AI Network Security Developer - Sr MTS
Overview
We are seeking a Cloud AI Network Security Developer to architect and deliver advanced AI-driven network security capabilities across multi-cloud environments.
You'll lead the design of Python/Go-based distributed systems that power intelligent firewalls, real-time telemetry analytics, and LLM-integrated threat automation.
This role combines deep knowledge of cloud networking, firewall technologies, data engineering, and AI model integration to create secure, adaptive, and self-learning security systems.
Key Responsibilities
- Architect, design, and implement Python/Go-based cloud microservices for network and security control plane.
- Lead development of next-generation firewall services policy enforcement, rule optimization, and AI-assisted event triage.
- Design and operationalize LLM integrations for:
- Policy generation and intent translation (natural language firewall rules)
- Incident summarization and contextual analysis
- AI-assisted troubleshooting and documentation
- Build streaming data pipelines to process large-scale flow logs, IDS/IPS alerts, and cloud telemetry in real time (Kafka, Flink, Pub/Sub, Kinesis).
- Develop AI/ML inference services for anomaly detection, threat scoring, and risk classification.
- Ensure secure service communication, policy compliance, and zero-trust alignment.
- Mentor junior engineers and guide design/code reviews.
- Collaborate with data scientists, AI engineers, and cloud networking teams to deliver production-grade features.
Required Skills
- Bachelor's or Master's degree in Computer Science, Cybersecurity, or related field.
- 6+ years of software development experience, with strong proficiency in Python/Go (Golang).
- Deep understanding of cloud networking (VPC/VNet design, routing, gateways, load balancers, overlays).
- Hands-on experience with firewall and security technologies:
- Policy engines and rule orchestration
- Deep Packet Inspection (DPI) and application-layer filtering
- NGFW/IDS/IPS systems
- Cloud-native firewalls (AWS Network Firewall, Azure Firewall, GCP Cloud Armor)
- Strong knowledge of data engineering pipelines real-time stream processing, event correlation, and log enrichment.
- Proven experience with AI/ML integration serving ML models via REST/gRPC, integrating LLMs for workflow automation, or building AI copilots for security.
- Solid experience in Kubernetes, microservices architecture, and observability systems (Prometheus, ELK, Grafana).
- Familiarity with security frameworks (Zero Trust, NIST CSF, CIS Benchmarks).
Nice to Have
- Experience in LLM application design (RAG, LangChain, vector databases).
- Expertise with network telemetry analytics and visualization systems.
- Contributions to open-source network security or AI frameworks.
- Knowledge of distributed systems scaling, resilient cloud design, and multi-cloud policy federation.
- Certifications such as AWS Security Specialty, GCP Cloud Security Engineer, CISSP, or CKA.
