Lead Network Observability Developer

Project description • As a Lead Network Observability Developer, you will be responsible for designing, developing, and maintaining AI/ML-based network observability and planning platform that enables collection, transformation, and correlation of network telemetry data from all Zurich's network service providers (NSP) • You will play a crucial role in modern software development and digital transformation strategies by ensuring that platform is high-performance, reusable, and reliable. Responsibilities Network observability platform: Design network observability platform and product architecture, based on best practices and scalable design patterns (reliability, availability, resilience, and fault tolerance) Schema: Develop schemas for source data transformation and standardization to Zeek format. Custom Analytics: Build custom analytics algorithms that deliver intelligent/predictive/insightful data. Data ingestion: Design and build modern data ingestion pipelines from NSP monitoring systems. Collaborate with Teams: Work with other software developers and business analysts to understand user needs and translate them into technical requirements. Testing and Troubleshooting: Test APIs to ensure responsiveness and efficiency and identify and fix bugs or bottlenecks. Documentation: Document development processes, standards, and guidelines for future reference and other developers. Technical Support: Provide technical support for APIs, including troubleshooting and problem resolution. Coaches and leads teams, as necessary. Experience in system and software security (SSO, Kerberos, LDAP, Windows AD, etc.), ensuring robust identity and access management. Application of engineering principles to production management, supporting scalable and efficient operations. Proven track record in automation, effectively reducing manual work and enhancing workflow productivity and consistency SKILLS Must have Programming Languages: Python, Go (Golang), C, C++, Java, PHP, JavaScript, ReactJS, HTML Backend & API Technologies: RESTful APIs, GraphQL, Kafka, Airflow, Microservices, Distributed Systems (HPC) Cloud & DevOps: AWS, GCP, Azure, Kubernetes, Docker, Terraform, CI/CD, Jenkins, Git, OpenTelemetry, Zeek Network Security Monitoring Tool Data & AI: Generative AI, AI Agents, LangChain, LLM, OpenAI, Machine Learning, Data Engineering, NLP, Elasticsearch, Vector Search, MySQL, PostgreSQL, Redshift, Spark, Hadoop, Hive Systems & Networking: Network Telemetry, TCP/IP, Linux Systems, Profiling & Performance Optimization Integration Skills: Experience in integrating APIs with existing systems. Architecture & Engineering Practices: Software Architecture, Design Patterns, SOLID Principles, Algorithms & Data Structures, Agile/Scrum, SDLC, Observability (ELK Stack, Grafana), Jira, Postman, Maven Critical Thinking Skills: Ability to troubleshoot and resolve issues efficiently. Attention to Detail: Strong eye for detail and a meticulous approach to development. Communication Skills: Excellent communication skills to collaborate with cross-functional teams. Nice to have • Strong understanding of reliability and production management, with a focus on maintaining high availability and stability across services. • Risk-aware mindset with knowledge of key operational risks in financial institutions, applying this insight to develop resilient and compliant solutions. • Promotes a culture of continuous improvement, driving proactive enhancements in processes and systems.