Software Engineering Manager

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.

Enterprise networking is evolving rapidly. Customers expect software that is intelligent, resilient, scalable, and increasingly autonomous. At AppLogic Networks, we are building the next generation of enterprise networking and analytics solutions, and we are looking for a Software Engineering Manager to lead the development of our Control Plane software.

This is an opportunity to lead a talented engineering team while directly influencing product strategy, system architecture, and customer success. We are looking for experienced engineers who have built enterprise networking or analytics products and are excited by solving complex distributed systems challenges while embracing Generative AI as an accelerator for modern software engineering.

Many organizations expect engineering managers to execute roadmaps.  At AppLogic Networks, we expect engineering leaders to help create them.  As a Software Engineering Manager, you will partner closely with Product Management, Architecture and Customer Success to define the capabilities that differentiate our products in the enterprise market.

 You will have the opportunity to influence: 

• Product vision and roadmap
• Platform architecture and scalability
• Customer experience
• Technology investments
• Engineering culture and execution
• Innovation through AI-enabled software development

Your ideas won't be buried under layers of process. They will directly influence products used by enterprise customers around the world. 

Modern software engineering is being transformed by Generative AI, and we believe engineering leaders should help define what that transformation looks like.  At AppLogic Networks, we are integrating AI across the engineering lifecycle to improve productivity, quality, design, testing, documentation, troubleshooting, and developer experience. 

We're looking for leaders who: 

• Regularly use Generative AI as part of their software development workflow.
• Understand how AI can improve engineering velocity while maintaining technical excellence.
• Encourage teams to adopt AI responsibly and effectively.
• Continuously experiment with new AI-powered development practices.
• View AI as a force multiplier for engineers, not a replacement for sound engineering judgment.

We are especially interested in candidates who can demonstrate how they've successfully incorporated AI into day-to-day engineering activities and team practices. 

• Lead the development of highly scalable Control Plane software for enterprise networking and analytics products.
• Build and mentor a high-performing engineering team focused on innovation, quality, and customer outcomes.
• Drive technical architecture, software design, and engineering execution.
• Partner closely with Product Management to define and prioritize customer-facing capabilities.
• Collaborate across engineering teams to ensure seamless integration between the Control Plane, Data Plane, OAM, and Product Platforms.
• Guide architectural decisions around distributed systems, scalability, resilience, security, and performance.
• Promote engineering best practices, automation, continuous delivery, and AI-assisted software development.
• Engage with customers and field teams to understand enterprise deployment challenges and translate them into product improvements.

We are looking for engineers who have developed enterprise infrastructure products used in demanding production environments.  You should have experience building one or more of the following: 

• Enterprise networking platforms
• Network security products
• Firewall or gateway management software
• Cloud-based network management platforms
• SD-WAN or SASE control systems
• Network orchestration and policy management platforms
• Distributed control systems
• Enterprise management and configuration platforms

• 7–12 years of software development experience building enterprise infrastructure software.
• Recent technical leadership or first-line engineering management experience.
• Strong software engineering skills in Python, Go, C++, or similar languages.
• Experience building distributed systems and highly available services.
• Strong understanding of APIs, microservices, event-driven architectures, and cloud-native development.
• Experience with Linux-based environments and containerized applications.
• Deep understanding of networking concepts including routing, switching, VPNs, security policies, and enterprise deployments.
• Strong architecture, design, and problem-solving skills.
• Practical experience using Generative AI to improve software engineering productivity and quality.

Previous management experience is helpful but not essential. Exceptional senior technical leaders looking to move into engineering management are encouraged to apply. 

Within your first year, you will: 

• Build and grow a high-performing engineering team.
• Deliver significant customer-facing capabilities.
• Improve platform scalability, reliability, and operational excellence.
• Help establish AI-enabled engineering practices across the team.
• Influence long-term product strategy and technical direction.
• Become a trusted technical leader across the organization.

Because they want: 

• Ownership of products and not just features.
• A direct voice in strategic technical decisions.
• Faster innovation with fewer organizational barriers.
• Opportunities to solve meaningful enterprise-scale problems.
• An engineering culture that embraces modern AI-powered software development.
• Close collaboration with product, architecture, and executive leadership.