2 hours ago
Base Salary
$250k - $351k/yr
Responsibilities
- Lead applied AI solution design and architecture for ambiguous business problems.
- Design distributed AI/ML systems and retrieval, prompting, tool-calling, and orchestration patterns.
- Develop and deploy AI-enabled workflows connecting enterprise systems, data sources, model APIs, and automation layers.
- Drive hands-on development of traditional and generative AI components.
- Lead MLOps pipelines for model training, versioning, deployment, and monitoring.
- Create evaluation approaches for output quality, retrieval accuracy, latency, and failure modes.
- Establish secure, reliable, observable, and maintainable AI application standards and reusable engineering patterns.
- Identify human-review requirements, controls, and escalation paths for responsible AI deployment.
- Collaborate with executive leadership, engineering, product, data science, security, and business stakeholders.
- Provide technical leadership and mentorship to AI/ML engineers.
- Research and evaluate emerging AI/ML techniques, algorithms, models, and tooling.
Requirements
- 10+ years of software or systems engineering architecture experience, including 4+ years building and deploying applied AI/ML systems in production.
- Bachelor’s degree in Computer Science, Engineering, or a related field; a Master’s or Ph.D. is a plus.
- Hands-on experience with generative AI, LLMs, Retrieval-Augmented Generation, context graphs, memory management, and agentic AI architectures.
- Strong programming skills in Python, Java, or Go.
- Deep proficiency with LangGraph, LlamaIndex, AutoGen, or Semantic Kernel, plus working knowledge of PyTorch or TensorFlow.
- Experience with vector databases such as Pinecone or Weaviate and graph databases such as Neo4j.
- Experience with distributed systems, event-driven streaming platforms, and cloud AI/ML platforms such as GCP Vertex AI, AWS SageMaker, or Azure OpenAI.
- Experience integrating applications, data sources, and internal platforms through APIs, services, event-driven patterns, or workflow tools.
- Understanding of AI security principles including prompt injection, data exfiltration, and RBAC, with experience in privacy- or compliance-constrained enterprise environments.
- Experience with telemetry, tracing, and production monitoring for AI systems, including tools such as LangSmith, Phoenix, or Datadog.
- Evidence of applied AI building through GitHub contributions, technical writing, demos, open-source work, publications, or AI engineering community participation.
- Prior solutions architecture experience bridging technical teams and senior business stakeholders.
Benefits
- The role is eligible for bonus potential, equity, and benefits.
- The U.S. base salary range is $250,400–$350,900, with the offer determined by location, skills, experience, education, and training.
Categories
About Rubrik
Rubrik builds an enterprise data security and backup platform that protects and recovers data, identities, and workloads across on-prem, public clouds, and SaaS. Its Rubrik Security Cloud delivers backup, ransomware detection and recovery, and policy management, sold primarily by subscription with professional services. Founded in 2014 and headquartered in Palo Alto, California, the company is publicly traded on the NYSE under the ticker RBRK.