Software Engineer II

AppLogic Networks powers the networks behind AI and the critical applications people rely on every day. We help network owners service providers and Enterprises understand how applications perform, how users experience them, and where action is needed to improve quality, efficiency, security, and profitability. Our software combines application intelligence, experience visibility, contextual insights, and real-time control to help customers elevate observability and do more with the networks they already run. As AI reshapes how the world works, connects, and communicates, AppLogic Networks helps ensure modern applications run smoothly across any network, from the consumer edge to the data center. Join our team and help build the software that makes networks smarter, more adaptive, and ready for what comes next.

Overview of the Role

AppLogic Networks delivers analytics platform capabilities focused on application identification, subscriber awareness, secure data handling, and large-scale network data processing. The Software Engineer II is responsible for developing new features for high performance network traffic simulation tools used to simulate customer environments for product system-level, functional and regression testing.

This role is responsible for the design and development of software features in a highly collaborative and fast-paced environment, working closely with Architects, Technical Leads, and Tests Engineers to deliver innovative features. You will be involved in the full software development lifecycle, from planning and design to implementation and documentation. You may assist in testing, debugging and modification of software. The role may include analysis of test results to ensure existing functionality and may make recommendations on corrective action

The role will contribute to backend services that support analytics workflows, data enrichment, secure API integrations, reporting, and platform scalability. The position requires strong backend engineering expertise, practical AI fluency, and working knowledge of React for frontend-backend collaboration. The engineer is expected to bring an innovation-driven mindset and contribute to building reliable, scalable, and secure platform components.

Key Responsibilities

• Design, develop, and maintain backend services for the Analytics Platform.
• Build scalable and secure applications using Python.
• Design and implement REST APIs with clear contracts, strong error handling, and reliable performance.
• Support platform scalability, high availability, failover, and active-active deployment patterns.
• Work with large-scale data flows, analytics workflows, reporting, and operational data processing.
• Collaborate with React frontend teams on API integration and backend support.
• Use AI tools to improve coding, debugging, testing, documentation, automation, and engineering productivity.
• Provide technical guidance on backend design, web development trends, scalable methodologies, and engineering best practices.
• Troubleshoot production issues across APIs, services, databases, infrastructure, and integrations.
• Work with DevOps teams on CI/CD, deployment automation, and production readiness.
• Participate in architecture reviews, code reviews, API reviews, and technical design discussions.
• Promote innovation, ownership, maintainability, and continuous improvement within the engineering team.

Qualifications

Knowledge and Skills

Required

• Strong hands-on experience in Python backend development.
• Strong understanding of SQL, database design, query optimization, and data access patterns.
• Exposure to Vertica for analytics and large-scale data querying.
• Good understanding of REST API design, authentication, authorization, versioning, and error handling.
• Experience with scalable backend architecture, distributed systems, and platform engineering.
• Knowledge of GoLang or Java.
• Understanding of failover, disaster recovery, and high-availability design.
• Working knowledge of React for API integration and frontend-backend collaboration.
• Experience with JSON APIs, secure system integrations, and HTTPS/TLS-based communication.
• Familiarity with Linux environments, containers, CI/CD, Git, automated testing, and deployment workflows.

Desired

• Practical fluency with AI coding assistants, prompt engineering, AI-assisted debugging, test generation, documentation, and automation.
• Awaren…