fulltime·Rubrik
Senior Applied AI Engineer
Bengaluru, IndiaEstimated ₹110 - 208 LPA9 skills
This is our market estimate, based on Levels.fyi Rubrik L5 Software Engineer India total comp. It is not the employer's disclosed pay.
Skills & Stack
PythonLangChainLangGraphRAGReactNext.jsREST APIsDistributed systemsPostgreSQL
About the Role
Senior full-stack engineer on Rubrik's Applied AI team shipping production AI-agentified features, agentic workflows and LLM-powered internal platforms.
About Rubrik
Cloud data security and AI operations company.
What You'll Do
- 1Own 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
- 2Build full-stack web applications: responsive, production-grade frontends using React/Next.js, backed by well-designed REST APIs and backend services
- 3Design and build APIs and services that are consumed by applications, internal tools, and AI agents/LLMs, including tool-calling interfaces
- 4Build 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
- 5Architect for distributed systems concerns: scalability, fault tolerance, data consistency, and service boundaries across backend and data layers
- 6Apply reliability engineering practices — observability (logging, metrics, tracing), SLAs/SLOs, incident response, and post-incident reviews — to keep production systems healthy
- 7Design and optimize relational database schemas, including joins, indexing, and query performance tuning
- 8Build clean, well-tested, production-grade frontend and backend code that others can read, test, and extend
What We're Looking For
- 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
- 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)
- 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)
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