Staff / Sr. Staff Engineer, AI Gateway

Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience.

About the Role

Netskope AI Gateway helps global enterprises securely adopt, scale, and govern Generative AI. We are seeking a Staff / Sr. Staff Software Engineer to architect, build, and scale the core systems powering our AI Gateway product and its supporting microservices across SaaS and on-prem/hybrid environments.

Based in Taiwan, you will be a technical anchor for our core development team. This is a hands-on, high-impact individual contributor role focused on building highly scalable backend systems, with real ownership: the systems assigned to you are yours to design, build, and defend — depth matters more than volume. You will operate at the intersection of deep distributed systems engineering and cutting-edge AI technology. We are looking for an engineering leader who leverages AI to accelerate their workflows, but possesses the rigorous, production-grade coding skills required to architect complex systems, ensure enterprise-grade security, and validate AI-generated code.

What You Will Be Doing

• Core Backend Development: Architect, build, and scale our core AI Gateway solutions, backend services, and high-throughput APIs. You will focus on writing highly concurrent, robust, and maintainable software, primarily in Golang.
• Command AI-Driven Engineering: Integrate AI and agent-based tooling (e.g., Copilots, code generators) into your daily development workflow to accelerate scaffolding, boilerplate, and hypothesis generation. Crucially, you will act as the gatekeeper: you must possess the deep software engineering expertise to audit AI-generated code, ensure architectural soundness, and reject code that introduces technical debt or security flaws.
• Design for Scale and Resilience: Build distributed systems capable of handling immense data payloads, streaming LLM responses (Server-Sent Events), and complex proxy routing without introducing unacceptable latency.
• Cross-Functional Collaboration: Partner directly with global engineering, AI researchers, and product teams. Translate ambitious AI features into scalable, maintainable software architectures. Raise system design considerations before a single line of feature code is written.
• Push Engineering Excellence: Drive the technical culture of the Taiwan team through architectural reviews, code reviews, and mentorship. Advocate for best practices in modern, AI-augmented software development, security, and scalable system design.
• Deep Systems Debugging: While not primarily an incident support role, you will be the ultimate escalation point for the hardest systemic development roadblocks. Trace complex issues across asynchronous microservices, Kubernetes networking layers, and TLS/Proxy protocols to architect permanent structural fixes.
• Share Production Ownership: Own what you ship — participate in the team's shared on-call rotation, monitor the health of your services, and turn recurring incidents into structural fixes.

What Success Looks Like

• Architectural Delivery: You translate ambiguous product requirements into clean, scalable, and secure Golang microservices that handle high throughput and streaming responses with minimal latency.
• AI-Augmented Technical Rigor: You consistently accelerate your output using AI coding tools, but the code you merge is rigorously vetted, secure, and architecturally sound, ensuring all hallucinations are caught.
• Elevating Engineering Standards: The technical excellence of the Taiwan team rises because of your presence. Your design documents, code reviews, and mentorship prevent systemic debt before feature code is written.
• Definitive Problem Solving: When complex cross-boundary roadblocks occur, such as proxy bottlenecks or async race conditions, you deliver definitive root causes and permanent structural fixes.
• Systemic Resilience: The AI Gateway maintains high availability and strict security enforcement while gracefully handling the evolution of major LLM provider APIs and scaling customer traffic.

Required Skills and Experience

• Engineering Experience: 8-10+ years in software engineering, with at least 5+ years deeply focused on backend development, cloud-native services, and distributed systems.
• Production-Grade Coding: Exceptional software engineering skills in Golang (highly preferred) or Python. You build modular libraries, reliable microservices, and scalable frameworks from scratch. You do not just prompt; you write software.
• AI-Assisted Workflow Proficiency: Demonstrated experience using advanced LLM-based coding agents in real engineering work. You understand where AI accelerates development and where it introduces technical debt or hallucinations, and you have a clear track record of catching what the AI misses.
• System Architecture: Expertise in microservices architecture, RESTful/gRPC API design, and navigating complex distributed system trade-offs (consistency vs. availability, caching strategies, asynchronous processing).
• Networking & Gateway Fundamentals: Deep understanding of Layer 4-7 networking: proxy architectures, HTTP/S, TLS interception, DNS, TCP/IP, and load balancing.
• Infrastructure & Kubernetes: Deep, hands-on experience developing for and debugging services on Docker/Kubernetes. You understand K8s networking, service discovery, and deployment strategies in cloud or hybrid environments.
• Autonomy & Communication: Track record of taking under-specified, ambiguous problems and driving them to working software solutions. Exceptional verbal and written English for complex technical collaboration across global teams.

Nice to Have

• GenAI Ecosystem: Familiarity with the request/response schemas of major LLM providers (OpenAI, Anthropic, Gemini), streaming formats, agentic protocols such as MCP and A2A, and orchestration frameworks like LangChain or LlamaIndex.
• Cybersecurity Domain: Background in Secure Web Gateways (SWG), Zero Trust Network Access (ZTNA), or Data Loss Prevention (DLP).
• Cloud Platforms: Experience developing and operating scalable services in AWS, GCP, or Azure.
• Event Streaming: Experience with message brokers and event-driven architectures (e.g., Apache Kafka).
• Observability: Strong grasp of embedding observability (OpenTelemetry, Prometheus, Grafana) directly into application code.

Education

• BS in Computer Science, Software Engineering, or equivalent practical experience required; MS strongly preferred.

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