Rubrik: Principal AI Architect — Palo Alto, CA

About Rubrik

Rubrik provides data-security and resilience technology for organisations facing cyberattacks, malicious activity and operational disruption. Its recruitment material discusses protecting enterprise information, including data held in business software and cloud environments. The described portfolio includes security and protection for SaaS applications, with attention to access, backup and recovery. Its business connects the technical handling of information with an organisation's ability to keep critical data protected and to recover when normal operations are disrupted.

The position and its setting

Rubrik lists Principal AI Architect in Palo Alto, CA, under reference 8223656. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Information Technology & Services
• Employer listing date: 30 September 2026

Responsibilities and work described

• At Rubrik IT, we are transforming how the enterprise thinks and operates — building a "thinking enterprise" where intelligent, agentic systems reason across our data, tools, and workflows to drive speed, quality, and measurable business impact
• As an AI Architect, you will be a pivotal technical leader driving AI Native solutions that make this vision real
• Operate where AI innovation, top-tier engineering, and business outcomes converge, acting as the technical bridge between complex business problems and cutting-edge AI execution
• Leveraging our robust Enterprise AI Platform, you will translate ambiguous problems into concrete AI solution designs and ensure their successful deployment and measurable impact
• Leadership: applied AI solution design and architecture, breaking down ambiguous business problems into concrete, actionable AI solution designs
• Contribution: to the detailed design of large-scale, distributed AI/ML systems, ensuring performance, reliability, and security
• Design: and improve retrieval, prompting, tool-calling, and orchestration patterns for internal use cases such as knowledge assistants, workflow automation, and decision support
• Champion and enforce design standards, patterns, and best practices for scalable and secure development of AI applications across teams
• Drive the hands-on development and implementation of key AI components, supporting both traditional and Generative AI model development and deployment
• Building: and deploy AI-enabled internal workflows that connect enterprise systems, data sources, model APIs, and automation layers
• Leverage AI-assisted development to accelerate implementation, bringing a 'editor' mindset to ruthlessly audit, review, and secure AI-generated code against our standards for reliability, security, observability, and documentation
• Leadership: the implementation and continuous improvement of MLOps pipelines, including automated model training, versioning, deployment, and monitoring
• Development: and maintain evaluation approaches for output quality, retrieval accuracy, latency, and failure modes, and use findings to improve system performance over time
• Help identify where human review, controls, and escalation paths are required to support responsible deployment of AI-enabled systems
• Apply sound engineering judgment to balance speed, usability, risk, and maintainability in production and near-production environments
• Proactively collaborate with executive leadership, data science, engineering, and product stakeholders to translate business use-cases into scalable AI solutions

Essential requirements and candidate background

• 10+ years of core Software/Systems Engineering architecture experience, including 4+ years dedicated to building and deploying applied AI/ML systems in production
• Direct hands-on experience with Generative AI technologies, including LLMs, Retrieval-Augmented Generation (RAG), context graphs, memory management, and agentic AI architectures
• Programming skills in Python, Java, or Go
• Deep proficiency with GenAI orchestration frameworks (e.g., LangGraph, LlamaIndex, AutoGen, Semantic Kernel) and a working knowledge of traditional ML frameworks (e.g., PyTorch, TensorFlow)
• Extensive hands-on experience with the modern AI data ecosystem, including Vector Databases (e.g., Pinecone, Weaviate) and Graph Databases (e.g., Neo4j)
• Experience: distributed systems architecture, event-driven streaming platforms, and cloud AI/ML platforms (e.g., GCP Vertex AI, AWS SageMaker, Azure OpenAI)
• Ability to work across data, model, application, and infrastructure layers, operating effectively with incomplete information and ambiguous problems
• Experience integrating applications, data sources, or internal platforms through APIs, services, event-driven patterns, or workflow tools
• Deep understanding of security principles as they apply to AI systems (e.g., prompt injection, data exfiltration, RBAC)
• Experience: enterprise-scale environments with meaningful privacy or compliance constraints
• Experience: telemetry, tracing, and production monitoring for AI systems (e.g., LangSmith, Phoenix, Datadog)
• Experience contributing to open-source AI projects, publications, or active participation in the AI engineering community
• Evidence of applied AI building — GitHub contributions, technical writing, demos, or open-source work demonstrating curiosity for emerging AI tooling
• Prior experience in a solutions architecture, successfully bridging technical teams and senior business stakeholders
• The minimum and maximum base salaries for this role are posted below; additionally, the role is eligible for bonus potential, equity and benefits
• The range displayed reflects the minimum and maximum target for new hire salaries for the role based on U.S. location
• Within the range, the salary offered will be determined by work location and additional factors, including job-related skills, experience, and relevant education or training
• US Pay Range
• $254,300 — $356,300 USD

Education and qualification routes

• Degree / qualification: Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s/Ph.D. is a plus)

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Advertised location: Palo Alto, CA

Conditions requiring the complete notice

Some passages contain complex or combined conditions that have not been reduced to short eligibility statements here. Read the complete linked notice for those passages, including any alternatives, exceptions or restrictions. The concise facts above should not be treated as the full wording of every condition.

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Principal AI Architect vacancy is not an offer for reference 8223656; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Rubrik

Applications follow the official employer page linked below.

Open the official Rubrik posting below and match the title and reference 8223656.

Compare your qualifications and experience with the essential conditions for the Palo Alto, CA position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• Java
• AWS
• GCP
• Azure
• APIs
• AI/ML
• LLMs
• Google Cloud
• AI
• audit
• compliance