Member of Technical Staff
Pure StorageSanta Clara, California
Full Time
Posted March 10, 2026
$149k - $224k
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Job Description
The role involves designing, developing, and deploying agentic AI solutions using large language models to drive enterprise automation and digital transformation, with a focus on secure, scalable, and reliable AI systems integrated into enterprise platforms.
Key Responsibilities
- Design and develop production-grade Agentic AI solutions using LLMs, multi-agent workflows, and RAG pipelines
- Implement and refine prompt engineering strategies, including structured prompts, tool-calling, and agent orchestration
- Build secure backend services and REST APIs in Python, integrating AI agents with enterprise systems using microservices architecture
- Establish robust guardrails such as output validation, fallback strategies, rate limiting, and safe tool invocation
- Develop and maintain model evaluation frameworks, including automated prompt testing, retrieval validation, and performance benchmarking
- Deploy and operate AI services on AWS, utilizing services like EC2, S3, Lambda, RDS, and containerization tools such as Docker and Kubernetes
- Apply security best practices including access control, data protection, audit logging, and secure API design
- Ensure observability, monitoring, and reliability of AI-driven services in production
Requirements
- 3 to 6 years of professional software engineering experience building backend or distributed systems.
- Strong proficiency in Python and developing RESTful APIs.
- Hands-on experience building LLM-based or Agentic AI applications, including RAG, embeddings, and vector database integrations.
- Practical experience in Prompt Engineering and understanding of LLM behavior, limitations, and optimization techniques.
- Experience deploying and operating applications in AWS cloud environments, including services such as EC2, S3, Lambda, RDS, and containerization using Docker and Kubernetes.
- Experience implementing AI guardrails, model validation techniques, and production monitoring.
- Solid understanding of cloud-native security practices and secure system design.
- Ability to design and develop production-grade Agentic AI solutions using LLMs, multi-agent workflows, and RAG pipelines.
- Ability to implement and refine Prompt Engineering strategies, including structured prompts, tool-calling, and agent orchestration to ensure reliable and deterministic AI behavior.
- Ability to build secure backend services and REST APIs in Python, integrating AI agents with enterprise systems using microservices architecture.
- Ability to establish robust guardrails, including output validation, fallback strategies, rate limiting, safe tool invocation, and human-in-the-loop patterns where appropriate.
- Ability to develop and maintain model evaluation frameworks, including automated prompt testing, retrieval validation, regression testing, and performance benchmarking.
- Ability to deploy and operate AI services on AWS, leveraging services such as EC2, S3, Lambda, RDS, and containerization tools like Docker and Kubernetes.
- Knowledge of strong security practices, including access control, data protection, audit logging, and secure API design.
- Ability to ensure strong observability, monitoring, and reliability of AI-driven services in production.
- Willingness to work from the Santa Clara, CA office in compliance with company policies, unless on PTO, work travel, or other approved leave.
Benefits & Perks
Salary range: 149,000 - 224,000 USD annually
Work environment: primarily in-office in Santa Clara, CA
Work schedule: flexible time off, with accommodations available for disabilities
Additional benefits: wellness resources, company-sponsored team events, potential incentive pay and equity, support for growth and development, inclusive and diverse workplace culture
Ready to Apply?
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