Sobre este puesto de Software Dev Engineer – Generative AI & Agentic Applications en SonicWall
SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter, 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 participate actively in code review.
- Document and hand-off: Produce clear technical documentation and runbooks so applications are supportable by the broader team.
Required Qualifications
- Experience: 6–8 years of professional software development experience, including building and shipping production applications.
- Programming: Strong proficiency in C# and .NET, plus solid REST/JSON API design skills.
- AI application development: Hands-on experience building applications that integrate LLMs — prompting, function/tool calling, RAG, and use of orchestration frameworks such as the Model Context Protocol (MCP).
- Testing: Practical experience with automated testing — unit, integration, and end-to-end — and a disciplined approach to quality assurance.
- Deployment: Experience with CI/CD pipelines (Azure DevOps), containerization (Docker), and deploying and operating applications in the cloud.
- Databases: Working experience with SQL and NoSQL databases (e.g., MongoDB); comfortable design schemas and writing efficient queries.
- Cloud fundamentals: Solid experience with Microsoft Azure, version control (Git), and observability/monitoring practices.
- Problem solving: Demonstrated ability to break down ambiguous requirements into a working, tested, and deployable solution.
- Communication: Strong written and verbal English; able to explain technical trade-offs clearly to both engineers and non-technical stakeholders.
Preferred Qualifications
- Agentic tooling: Experience with the Model Context Protocol (MCP), LangChain, LangGraph, or comparable agentic orchestration frameworks.
- AI platform: Familiarity with Azure AI Foundry (good to have).
- LLM platforms: Practical experience with Anthropic Claude, Claude Code, or the Claude Agent SDK, or equivalent LLM provider platforms.
- Vector search: Experience with vector databases (e.g., Pinecone, Weaviate) and retrieval pipeline design.
- Containers & orchestration: Familiarity with Kubernetes (e.g., Azure Kubernetes Service) or similar container-orchestration platforms.
- Enterprise applications: Familiarity with Salesforce, Snowflake, Oracle EBS, or similar enterprise application landscapes.
- Industry background: Experience in security, SaaS, or B2B technology sectors.
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SonicWall is an equal opportunity employer.
We are committed to creating a diverse environment and are an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, color, ethnicity, religion, sex, gender, gender identity and expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis prohibited by applicable law.
At SonicWall, we pride ourselves on recruiting a diverse mix of talented people and providing active security solutions in 100+ countries.
