Software Engineer - Agentic AI & Automation

Pure Storage•Santa Clara, CA

4h•Onsite

About The Position

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. Pure Storage is a leader in modern data storage, providing enterprise data cloud solutions that power mission-critical workloads globally. As part of the Digital Transformation organization focused on the G&A domain, you will use your software engineering expertise to design, build, and run production-grade AI and automation solutions on top of large-scale enterprise platforms. You will work closely with engineers, internal services technology teams, and business stakeholders to identify high-impact opportunities and deliver robust, secure, and maintainable agentic AI capabilities. This is a high-visibility role that will shape the future employee experience at Pure.

Requirements

Bachelor’s or Master’s in Computer Science, Computer Engineering, or related field, or equivalent experience.
5+ years of professional software engineering experience building and operating production systems.
Strong programming skills in Python and at least one additional language (e.g., Java, Go), plus solid knowledge of data structures and algorithms.
Hands-on experience with enterprise platforms such as ServiceNow, Snowflake, Boomi, Workday, Salesforce, or similar.
Practical experience with agentic AI / LLM-based applications, including multi-agent systems, RAG pipelines, vector databases, or tool/agent integrations with enterprise APIs.
Experience developing robust integrations and APIs to extend platform capabilities and enable end-to-end automation.
Strong analytical, communication, and collaboration skills, with a proactive, ownership-driven approach to problem solving.

Responsibilities

Design and develop agentic AI solutions, including AI agents, orchestration services, and integrations with enterprise systems.
Build and deploy AI applications using LLMs, agentic frameworks, and modern software engineering practices (testing, observability, CI/CD).
Implement agentic workflows within enterprise platforms such as ServiceNow, Glean, and related systems.
Develop multi-agent systems, RAG pipelines, and vector database integrations to deliver accurate, context-aware experiences.
Integrate and orchestrate enterprise tools (e.g., ServiceNow, Snowflake, Boomi, internal APIs) to drive automation and process efficiency.
Collaborate with platform, data, and application teams to define standards and patterns for AI and automation across internal services.