Senior Software Engineer – Generative AI & Agentic Applications

For more than 30 years, SonicWall has delivered a partner-first unified cybersecurity portfolio that helps SMBs, MSPs, and IT teams consolidate network security, endpoint security, security service edge (SSE), and threat response across hybrid environments. By bringing connected technology, real-time threat intelligence, automation, and expert services together, SonicWall helps organizations simplify security operations, achieve better security outcomes, and lower total cost of ownership. Backed by a global ecosystem of more than 17,000 partners, SonicWall delivers enterprise-grade protection built for SMB and mid-market realities. For more information, visit www.sonicwall.com or follow us on X, LinkedIn , Facebook , and Instagram . Position Summary We are hiring a Software Dev Engineer to design, build, test, and deploy AI-powered applications. You will work across the full application lifecycle — from architecture and implementation through automated testing, CI/CD deployment, and production monitoring — building features that put large language models and agentic tooling to work inside SonicWall's internal systems. This is a hands-on engineering role for someone with 6–8 years of professional software development experience who is comfortable owning services end to end: writing production-quality code, integrating LLM and agentic APIs, standing up reliable data and retrieval pipelines, and shipping through a disciplined test-and-release process. You will collaborate closely with senior engineers, product stakeholders, and platform teams to turn requirements into dependable, well-tested applications. Key Responsibilities Develop AI applications: Design and build features and services that use LLM and agentic capabilities — prompting, tool/function calling, retrieval-augmented generation (RAG), and orchestration — to solve real internal business problems. Write production code: Implement clean, maintainable, well-documented backend and integration code in C# and .NET, following established architecture and coding standards. Test thoroughly: Write unit, integration, and end-to-end tests; build and maintain automated test suites; validate output quality and correctness for AI-driven features before release. Deploy and operate: Package, deploy, and support applications through CI/CD pipelines; monitor performance, reliability, and cost in production; troubleshoot and resolve issues quickly. Integrate with enterprise systems: Connect applications to internal and third-party systems and data sources via REST/JSON APIs, MCP servers, and the iPaaS layer, respecting access controls and data-handling rules. Engineer for quality and safety: Implement evaluation, guardrails, logging, and observability so AI features behave predictably and safely at production scale. Collaborate cross-functionally: Work with senior engineers, product owners, and business stakeholders to translate requirements into technical designs, and…