Senior Applied AI Engineer

About the Role

We are looking for a Senior Applied AI Engineer to join Rubrik's Applied AI team, building production-grade, full-stack applications and APIs for our internal Business teams while embedding AI-agentified capabilities into these internal platforms. This is a hands-on build role: you will own features end to end — from database schema through backend services and distributed systems to the user interface — and bring practical, hands-on experience building or integrating AI agents, tool-calling workflows, or LLM-powered features into production systems that our business stakeholders rely on.

The ideal candidate combines strong full-stack engineering fundamentals with a systems mindset for reliability and scale, and has spent meaningful hands-on time (1–2 years) building AI-agentified applications — not just experimenting with AI tools, but shipping agentic features in production. We are targeting 8+ years of overall software engineering experience; this is flexible for candidates who demonstrate strong depth across full-stack, distributed systems, and applied AI during technical evaluation.

Key Responsibilities

- 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.

- Build full-stack web applications: responsive, production-grade frontends using React/Next.js, backed by well-designed REST APIs and backend services.

- Design and build APIs and services that are consumed by applications, internal tools, and AI agents/LLMs, including tool-calling interfaces..

- Build and productionize AI-agentified features — agentic workflows, LLM-powered automation, and AI-assisted tooling — grounded in 1–2 years of hands-on experience with these systems.

- Architect for distributed systems concerns: scalability, fault tolerance, data consistency, and service boundaries across backend and data layers.

- Apply reliability engineering practices — observability (logging, metrics, tracing), SLAs/SLOs, incident response, and post-incident reviews — to keep production systems healthy.

- Design and optimize relational database schemas, including joins, indexing, and query performance tuning.

- Build clean, well-tested, production-grade frontend and backend code that others can read, test, and extend.

- Clarify requirements upfront, surface blockers early, and communicate progress proactively without being asked.

- Collaborate openly with internal Business stakeholders, Product, QA, DevOps, and UX or designer teams; avoid working in silos.

Required Qualifications

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-agentified 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-agentified 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 fr