Pure Storage is seeking an Agentic AI Software Engineer to build production-grade agentic AI solutions that drive enterprise automation and digital transformation. You will design and deploy LLM-based services, implement prompt engineering techniques, guardrails, and model evaluation frameworks, ensuring secure, scalable delivery on AWS.

What You'll Do

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, including output validation, fallback strategies, rate limiting, safe tool invocation, and human-in-the-loop patterns.
Develop and maintain model evaluation frameworks, including automated prompt testing, retrieval validation, regression testing, and performance benchmarking.
Deploy and operate AI services on AWS, leveraging services such as EC2, S3, Lambda, RDS, and containerization using Docker and Kubernetes.
Apply strong security best practices, including access control, data protection, audit logging, and secure API design.
Ensure strong observability, monitoring, and reliability of AI-driven services in production.

What We're Looking For

3–6 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.
Experience implementing AI guardrails, model validation techniques, and production monitoring.
Solid understanding of cloud-native security practices and secure system design.

Nice to Have

Experience with multi-agent orchestration frameworks or AI tool integration patterns.
Familiarity with vector databases such as Pinecone, Weaviate, OpenSearch, or similar.
Experience with CI/CD pipelines and containerized deployments using Docker and Kubernetes.
Exposure to enterprise platform integrations such as ServiceNow, Snowflake, or similar systems.
Familiarity with observability tools such as Datadog, Prometheus, or similar platforms.

Technical Stack

Python, REST APIs, LLMs, Multi-agent workflows, RAG pipelines
AWS, EC2, S3, Lambda, RDS
Docker, Kubernetes, Microservices architecture

Benefits & Compensation

Compensation range: $149,000—$224,000 USD
Flexible time off
Wellness resources
Company-sponsored team events

Work Mode

This is an onsite position based in Santa Clara, CA.

Pure Storage is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other characteristic legally protected by the laws of the jurisdiction in which you are being considered for hire.