Senior Curriculum Engineer — Field & Technical Enablement

MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data.

The MinIO team is looking for a technically strong curriculum engineer who is equally at home on a sales call and building with the technology underneath it — whether that's a data pipeline or an agentic AI stack. In this role, you'll build and deliver training across the full spectrum of MinIO's technical audience — from storage administrators learning to operate AIStor in production, to field architects preparing for competitive enterprise deals, to partners who need to sell and position MinIO products effectively.

This role has real variety. On any given week, you might be building a hands-on lab, standing up an agent memory demo, delivering a live enablement session for field architects, adapting a sales deck into a teachable module for partners, or wrapping our core curriculum in a use-case narrative for a specific deployment context. You enjoy that variety. You're as comfortable in front of a room of FAs as you are at a command line.

You will collaborate closely with engineering, product marketing, sales leadership, and the field. You welcome the freedom and opportunity of being part of a startup and have the self-discipline to identify needs and get things done without waiting to be asked. You will be encouraged to help shape the strategy that the MinIO team executes.

Previous experience in a field architect, solutions architect, or technical sales role is required — you need to understand how FAs think, what they need in a competitive engagement, and how to make training land in that context. Previous experience with competitive software-defined storage platforms is strongly preferred. Strong oral and written communication skills are essential.

What You Will Do

Design and deliver field architect curriculum — equipping FAs and Customer Engineers (CEs) with the technical depth and competitive positioning fluency needed to win enterprise deals

Deliver live and recorded enablement sessions for field architects and, occasionally, non-technical sales audiences

Develop partner sales curriculum by translating sales and marketing content into structured, teachable modules for partner and reseller audiences

Build core curriculum for customer administrators and operators — covering installation, configuration, management, and troubleshooting

Create use-case "wrappers" that reframe core curriculum content for specific deployment contexts and horizontal use cases, with references to vertical specifics where relevant

Build curriculum for AIStor Memory and agentic AI use cases, translating orchestration and memory concepts (context assembly, agent state, retrieval) into competitive, FA-ready training

Contribute to special projects requiring hands-on technical skill across a broad range of technologies including Linux, Ansible, Python, Kubernetes, and agentic AI frameworks (e.g., LangChain/LangGraph, vector/memory stores)

Build real-world, use case–driven hands-on labs that establish best practices for deploying and operating MinIO products

Apply prior experience with competitive storage platforms to inform differentiated, insight-rich training content

Package labs and content into short, outcome-oriented training modules with videos

Record engaging videos of modules for MinIO Academy, YouTube, and LinkedIn

What You Will Bring

5+ years in a field architect, solutions architect, technical sales engineer, or equivalent customer-facing technical role

3+ years of experience with software-defined storage including hands-on experience with MinIO, AWS S3, or competitive storage platforms (Vast, Cloudian, Weka)

1+ years of experience with agentic AI infrastructure (e.g., agent memory/orchestration platforms such as LangChain/LangGraph, Mem0, Letta, AWS Bedrock AgentCore, Google Vertex AI Memory Bank);

or memory/vector infrastructure (Pinecone, Weaviate, Redis) strongly preferred

3+ years using Amazon AWS, including a solid understanding of S3 and the S3 API

3+ years working in a Kubernetes environment