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Rubrik is seeking a Senior Applied AI Engineer to join its Applied AI team, building production-grade, full-stack applications and APIs for internal business teams while embedding AI-agentic capabilities into internal platforms. This is a hands-on, end-to-end ownership role: you will own features from database schema through backend services and distributed systems to the user interface, bringing practical experience building or integrating AI agents, tool-calling workflows, or LLM-powered features into production systems that business stakeholders rely on.
You will own features end-to-end—database schema, backend services, APIs, and frontend (React/Next.js) user interface—operating as an owner rather than a ticket-taker. Key responsibilities include building full-stack web applications with responsive, production-grade frontends using React/Next.js backed by well-designed REST APIs and backend services; designing and building APIs and services consumed by applications, internal tools, and AI agents/LLMs, including tool-calling interfaces; building and productionizing AI-agentic features grounded in 1–2 years of hands-on experience; architecting for distributed systems concerns such as scalability, fault tolerance, data consistency, and service boundaries; applying reliability engineering practices including observability, SLAs/SLOs, incident response, and post-incident reviews; designing and optimizing relational database schemas; building clean, well-tested, production-grade code; clarifying requirements upfront and surfacing blockers early; and collaborating openly with internal business stakeholders, product, QA, DevOps, and UX/designer teams.
Rubrik is the Security and AI Operations Company, leading at the intersection of data protection, cyber resilience, and enterprise AI acceleration. Rubrik Security Cloud delivers complete cyber resilience by securing, monitoring, and recovering data, identities, and workloads across clouds. Rubrik Agent Cloud accelerates trusted AI agent deployments at scale by monitoring and auditing agentic actions, enforcing real-time guardrails, and fine-tuning for accuracy.
**Requirements:**
*Education & Experience:*
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
- 8+ years of hands-on software engineering experience across full-stack development (flexible based on demonstrated strength in technical evaluation)
- 1–2 years of hands-on experience building, integrating, or operating AI-agentic applications (agentic workflows, tool-calling, RAG, or LLM-powered features) in production
- Demonstrated experience owning systems designed for scale and reliability, not just feature delivery
*Technical Skills — Applied AI:*
- 1–2 years of hands-on experience building AI-agentic applications, including agent frameworks (e.g., LangChain, LangGraph, ADK, or equivalent), tool/function-calling for LLMs
- Practical understanding of AI-specific considerations: latency, cost, rate limiting, and safety/guardrails when exposing systems for AI consumption
- Experience with AI-assisted development tools (e.g., Claude Code or similar)
*Technical Skills — Full Stack:*
- Frontend: Strong JavaScript fundamentals; hands-on experience with React and Next.js for building modern, production-grade web applications (hooks, state management, component architecture, routing/SSR)
- Backend: Proficient in Python, writing production-grade code; hands-on experience with FastAPI or Flask (or equivalent frameworks) for building REST APIs
- Database: Experience with relational and non-relational databases (PostgreSQL, MySQL, SQL Server, MongoDB or equivalent); solid understanding of schema design, joins, indexing, and query optimization
*Technical Skills — Distributed Systems & Reliability:*
- Working knowledge of distributed systems concepts: service decomposition, consistency models, caching, queuing/messaging, and failure handling
- Reliability engineering fundamentals: observability (logging, metrics, tracing), SLAs/SLOs, error budgets, and operational runbooks
- Ability to reason about system design trade-offs and build scalable, resilient solutions under ambiguity
*Soft Skills:*
- Proactive communication—shares updates without being asked and flags blockers early
- Asks the right questions—clarifies requirements upfront before jumping into implementation
- Ownership mindset—treats the project as their own rather than just completing tickets
- Transparency—speaks up when something is unclear instead of making assumptions
- Strong analytical mindset to break down complex or ambiguous problems
*Preferred Qualifications:*
- Experience with agentic frameworks (ADK, LangGraph, or similar) beyond individual projects—production deployment experience preferred
- Familiarity with API documentation standards (Swagger/OpenAPI)
- Basic DevOps awareness (Docker, CI/CD) and Git/version-control best practices
- Testing experience across unit and integration levels
- Experience with modern web app tooling—component libraries (e.g., Tailwind, MUI) and state management (e.g., Redux, Zustand)
- Exposure to cloud-native development (AWS, Azure, or GCP), including containers and infrastructure as code
