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Sr AI Engineer, Agentic Systems

Rubrik · Posted Oct 28

Cloud data security, zero-trust backup, threat analytics, and cyber resilience services

Bengaluru, IndiaFull-timeOnsiteSenior Level7+ years₹50.0L–₹80.0L yearly<25 applicants
Cloud ComputingCybersecurityData ManagementSaaSArtificial IntelligencePublic Company
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About the role

Rubrik's Enterprise AI Incubation team builds and proves agentic AI systems on Rubrik itself, aiming to create a thinking enterprise where applications learn from company data and act through agents. The role is a senior full-stack AI engineering position focused on shipping production agents, multi-agent workflows, tool integrations, evaluations, and guardrails. This engineer will own agent systems end to end, from workflow discovery and architecture through coding, deployment, and production operation.

What you will do

  • Lead product discovery alongside Product Managers and domain experts to understand real workflows, map them out, and define clear problems, baselines, and success criteria as the foundation for building agentic solutions.
  • Design, build, test, and deploy production agents, automations, and internal tools using coding agents, LLM APIs, and agent frameworks, integrated with Rubrik’s internal agent platform and business systems.
  • Turn complex processes into multi-agent workflows that carry real work and make decisions: orchestrators that qualify and routes deals, workers that move orders through approval and fulfillment under business rules, agents that monitor signals and recommend actions for customer health, or coordinated agents that handle hire-to-retire steps across HR, IT, and managers with shared state and clear handoffs.
  • Engineer agents for autonomy with reliability, including tool and orchestration flows, context management, caching, retries, and failure handling.
  • Leverage full-stack engineering across backend services, APIs, data models, interactive screens, approval UIs, and chat interfaces as the complete medium to deliver high-ownership, user-facing agent systems.
  • Apply solid software engineering practices to AI systems, treating prompts, skills, configs, and specs as versioned artifacts, with code review, tests, CI or CD, and staged rollouts.
  • Implement evaluation, guardrails, and quality control: derive evals from workflow data, establish quality gates and guardrails, integrate human-in-the-loop approvals where needed, and monitor production runs to refine agents over time.
  • Use measured results to decide how to evolve or retire agents, and turn successful systems into patterns and libraries that can be reused.

Skills used in this role

What the employer is looking for

  • Around 7 or more years of professional software engineering experience in production systems, and around 2 or more years of professional, hands-on experience building AI agents and agent powered production applications with measurable outcomes.
  • Strong full stack engineering background, with a track record of designing, building, and owning services end to end, including backend APIs and integrations, data models, and user facing interfaces such as approval UIs, dashboards, or chat surfaces.
  • A builder mindset: comfortable defining baselines and metrics, reporting results in business terms, working in a fast moving environment, and closing the loop by building, demoing, learning, and building again. If you like seeing improvements in hours saved, errors avoided, and teams unblocked, you will have plenty of chances to measure that here.
  • System design: break down complex problems, design APIs and data models, reason about latency, throughput, and failure modes, and choose simple, robust architectures.
  • Algorithms, data structures, access control permissions, and data provenance.
  • Spec driven development: turn vague requirements into clear problem statements, write or refine design docs, and use a Spec → Plan → Task → Code→ Converge flow so work is traceable from design to code, including when you use AI coding agents.
  • Execution discipline: use version control, code review, automated tests, CI or CD, staged rollouts and rollbacks, logging, metrics, and tracing, and improve systems based on issues and signals from production.
  • Build agents in code using LLM APIs, SDKs, and libraries, not just no code or low code tools, and have shipped agentic systems that real users rely on.
  • Design robust agent harnesses and multi agent orchestrations: model tools and resources, manage context and state, and keep runs reliable under real world data and load.
  • Establish continuous evaluation and safety mechanisms: turn production failures into test cases, gate changes on eval suite results, and enforce guardrails across agent workflows.
  • Exercise clear judgment on AI fit: decide when a problem needs an agent versus a simpler automation or no build, and make tradeoffs around model choice, latency and cost, context strategy, and autonomy using data rather than intuition.

Preferred qualifications

  • Knowledge/context graphs: entities and relationships, GraphRAG, hybrid retrieval.
  • Agent frameworks and runtimes: Google ADK, LangGraph, OpenAI style, cloud or container platforms.
  • Backend: Python, FastAPI or similar stacks.
  • Tools integration: MCP, Slack or Teams bots, REST APIs, webhooks.
  • Data systems: Snowflake, Salesforce, graph stores.
  • UX: conversational flows, chat surfaces, guided forms, simple dashboards for agent output.

Benefits and support

  • Compensation and benefits are detailed in the job posting

About Rubrik

Rubrik logo

Rubrik

Company website
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Rubrik is a cloud-native cybersecurity and data resilience company that provides zero-trust data protection, threat monitoring, and automated enterprise recovery solutions. The company delivers a unified platform designed to safeguard hybrid and multi-cloud environments against ransomware and malicious cyber threats. By integrating AI-driven operations and risk analytics, Rubrik helps enterprises ensure business continuity and digital trust.

Industry
Cloud Computing
Company size
3000-5000 employees
Founded
2014
Location
Palo Alto, California, USA
Funding stage
Public Company

Funding

Public Company · $553M raised

Greylock PartnersLightspeed Venture PartnersMicrosoftKhosla VenturesInstitutional Venture Partners (IVP)
  • 2021-08-17Series FUndisclosed
  • 2021-11-01Secondary Market$1.3M

Leadership

BS
Bipul Sinha

Co-Founder, CEO and Chairman

AN
Arvind Nithrakashyap

Co-Founder and CTO

KC
Kiran Choudary

Chief Financial Officer

AG
Anneka Gupta

Chief Product Officer

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