SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 254,300 - 356,300 / annual
Rubrik is seeking an AI Architect to lead the design and deployment of AI-native solutions across the enterprise. This is a pivotal technical leadership role where you will operate at the intersection of AI innovation, top-tier engineering, and measurable business outcomes.
You will serve as the technical bridge between complex business problems and cutting-edge AI execution, leveraging Rubrik's Enterprise AI Platform to translate ambiguous problems into concrete AI solution designs. This role is designed for systems-thinkers with an AI-first mindset who move fluidly between hands-on AI solution building and orchestrating model APIs, data sources, and workflow layers.
Key responsibilities include:
- Lead applied AI solution design and architecture, breaking down business problems into actionable AI designs
- Contribute to 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 knowledge assistants, workflow automation, and decision support
- Champion design standards, patterns, and best practices for scalable AI application development across teams
- Drive hands-on development and implementation of key AI components, supporting both traditional and Generative AI model development
- Build and deploy AI-enabled internal workflows connecting enterprise systems, data sources, model APIs, and automation layers
- Lead MLOps pipeline implementation and continuous improvement, including automated model training, versioning, deployment, and monitoring
- Develop and maintain evaluation approaches for output quality, retrieval accuracy, latency, and failure modes
- Identify where human review, controls, and escalation paths are required for responsible AI deployment
- Provide technical leadership and mentorship to other AI/ML engineers, fostering engineering excellence
- Collaborate with executive leadership, data science, engineering, and product stakeholders to translate business use-cases into scalable solutions
- Actively research and evaluate cutting-edge AI/ML techniques and models for platform enhancement
Requirements:
- 10+ years of core Software/Systems Engineering architecture experience, including 4+ years dedicated to building and deploying applied AI/ML systems in production
- Bachelor's degree in Computer Science, Engineering, or related field (Master's/Ph.D. preferred)
- Direct hands-on experience with Generative AI technologies including LLMs, Retrieval-Augmented Generation (RAG), context graphs, memory management, and agentic AI architectures
- Strong programming skills in Python, Java, or Go with deep proficiency in GenAI orchestration frameworks (LangGraph, LlamaIndex, AutoGen, Semantic Kernel) and working knowledge of traditional ML frameworks (PyTorch, TensorFlow)
- Extensive hands-on experience with modern AI data ecosystem including Vector Databases (Pinecone, Weaviate) and Graph Databases (Neo4j)
- Experience with distributed systems architecture, event-driven streaming platforms, and cloud AI/ML platforms (GCP Vertex AI, AWS SageMaker, Azure OpenAI)
- Strong ability to work across data, model, application, and infrastructure layers 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 for AI systems (prompt injection, data exfiltration, RBAC) with experience in enterprise-scale environments with privacy or compliance constraints
- Experience with telemetry, tracing, and production monitoring for AI systems (LangSmith, Phoenix, Datadog)
- Evidence of applied AI building through GitHub contributions, technical writing, demos, or open-source work
- Prior experience in solutions architecture successfully bridging technical teams and senior business stakeholders
