---
title: 'Field Architect at MinIO'
canonical: 'https://feeny.ai/job/field-architect-minio-riyadh-gfxmy5zh56pv'
type: 'job'
last_seen: '2026-10-20'
---

# Field Architect at MinIO

- **Company:** MinIO
- **Location:** Riyadh, Saudi Arabia
- **Work type:** remote
- **Posted:** 2026-10-06
- **Last confirmed live:** 2026-10-20
- **Apply:** https://job-boards.greenhouse.io/minio/jobs/5441713008

## Job description

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 Field Architect role at MinIO is a senior customer-facing technical position focused on defining, validating, and guiding architectures for AI, analytics, cloud-native applications, and large-scale data platforms. You will serve as a trusted technical advisor to customers, partners, and internal teams, translating business and application requirements into robust technical designs that deliver measurable outcomes.

You will collaborate closely with the broader MinIO team through technical discovery, architecture design, proof-of-concept (PoC) delivery, production onboarding, performance validation, and long-term expansion. Success in this role requires hands-on expertise across the data stack, strong architecture and communication skills, and ownership of customer technical outcomes.

What You Will Do:

Technical Leadership & Architecture

- Technical Architecture and Discovery: Lead technical discovery with customers and partners to understand their business goals, data sources, application requirements, infrastructure constraints, and success criteria. Design end-to-end architectures that address those requirements.
- Data Platform Architecture: Design solutions across the full data stack, including ingestion and change data capture (CDC), batch and streaming pipelines, data processing, lakehouse storage and table formats, catalogs, query and analytics engines, orchestration, data quality, governance, and AI integration. Understand how these components work together and guide customers through architecture decisions and tradeoffs.
- AI and Analytics Workload Design: Define and validate architectures for AI/ML training and inference, analytics, lakehouse environments, high-performance data pipelines, and modern application data services.
- Object Storage and S3 Expertise: Serve as a subject matter expert in AIStor, object storage, S3-compatible architectures, distributed systems, replication, erasure coding, security, performance tuning, and large-scale namespace design.

Customer Engagement & PoC Delivery

- Customer Technical Advisor: Build trusted relationships with customer technical stakeholders across data engineering, analytics, AI, infrastructure, platform, security, application, and operations teams. Guide customers toward informed architecture decisions.
- PoC Ownership and Delivery: Plan and conduct customer PoCs from initial scope through final technical review. Agree on success criteria, design and deploy the solution, integrate the required data stack components, build representative use cases, run functional and performance tests, troubleshoot issues, document results, and drive the PoC to a clear outcome and production plan.
- Customer Success Beyond the Win: Partner with Customer Engineering, Product Management, and Engineering to help customers move from PoC to production and expand adoption across additional workloads and teams.

Ecosystem, Enablement & Field Operations

- Cloud-Native and Kubernetes Guidance: Provide technical leadership on Kubernetes, containers, automation, and deployment patterns across private, public, and hybrid cloud environments.
- Solution Integration: Work with customer teams and technology partners to integrate data sources, ingestion and streaming tools, processing and analytics engines, AI platforms, identity systems, observability tools, and infrastructure components.
- Technical Presentations and Enablement: Deliver architecture presentations, whiteboard sessions, demonstrations, workshops, and technical enablement for customers, partners, and internal teams.
- RFP, RFI, and Technical Response Support: Lead or contribute to technical responses covering the full data platform, including architecture, integrations, security, scalability, performance, and operational requirements.

Product Intelligence & Market Expertise

- Product and Engineering Feedback: Capture customer requirements, PoC findings, integration needs, and field feedback. Work with Product and Engineering teams to resolve gaps and inform priorities.
- Competitive and Market Expertise: Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competing data platforms. Explain technical differentiation in the context of customer use cases.

Your Skills and Experience:

- 10+ years of experience in a senior customer-facing technical role such as Field Architect, Solutions Architect, Sales Engineer, Systems Engineer, or Technical Consultant.
- Hands-on experience designing, integrating, and troubleshooting end-to-end data platforms. This should include several of the following: ingestion, CDC, batch and streaming processing, lakehouse architecture, catalogs, query engines, orchestration, data quality, governance, and AI/analytics workloads.
- Demonstrated experience leading customer PoCs, including defining success criteria, deploying and integrating components, validating functionality and performance, resolving technical issues, and presenting results.
- Strong understanding of object storage and S3-compatible architectures, including security, replication, data protection, performance, and scale-out design.
- Hands-on experience with Linux, networking, storage systems, containers, Kubernetes, and modern data center infrastructure.
- Practical experience with relevant data stack technologies, such as Kafka, Debezium, NiFi, Spark, Flink, Trino, Starburst, Iceberg, Delta Lake, or data catalogs. Experience with every listed technology is not required.
- Experience designing or supporting AI, machine learning, analytics, lakehouse, or large-scale data pipeline environments.
- Experience with public and hybrid cloud environments, including AWS, Azure, GCP, OCI, or private cloud platforms.
- Ability to lead technical discovery, design architectures, build demonstrations, analyze performance, troubleshoot integrations, and communicate tradeoffs clearly.
- Strong verbal, written, whiteboarding, and presentation skills, with the ability to communicate with both technical and executive audiences.
- Ability to work collaboratively across customers, partners, Sales, Product, Engineering, and Customer Engineering teams.
- Strong customer-success orientation, intellectual curiosity, sense of ownership, and ability to prioritize effectively in a fast-moving environment.
- Willingness to travel as needed to support customers, partners, field events, and internal team activities.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field; equivalent practical experience will also be considered.

## Equal Opportunity Policy (EEO)

MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

## About MinIO

## Company Overview
- **One-liner**: MinIO provides high-performance, S3-compatible object storage purpose-built for AI, analytics, and cloud-native workloads.
- **Entity Type**: Private (Series B; total funding $126.3M, last round $103M raised ~4 years ago)
- **Headquarters**: Redwood City, California, United States
- **Founded**: 2014
- **Founders**: Garima Kapoor, Anand Babu “AB” Periasamy, Harshavardhana

## Core Business
- **Primary industry**: Data Infrastructure / Object Storage
- **Target customers**: B2B, Enterprise (77% of the Fortune 500 use MinIO), AI/ML teams, analytics platforms
- **Mission**: Remove every barrier between organizations and their data, enabling secure, sovereign, AI-ready infrastructure.

## Products & Services
- **[MinIO AIStor](https://www.min.io/)**: High-performance object store with native S3 compatibility, consistent sub-10ms latency, exabyte-scale scalability, and 99.999999999% durability. Designed for AI training, inference, and analytics. Includes zero-touch operations, self-healing architecture, and 40% lower TCO.
- **Context Memory for AI Inference**: Purpose-built memory layer that delivers 95%+ GPU utilization, 50% lower cost per token, and average savings of $2M per 100 GPUs.

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private company)
- **Key Metric**: $126.3M total funding raised (Series B, last round $103M)
- **Notable Investors/Partners**: Investors listed on company site but not named in public summaries; strategic partner Databricks (named 2026 ISV Storage Partner of the Year)
- **Growth Signals**:
  - 77% of the Fortune 500 use MinIO
  - 32.9K+ GitHub stars, 53.3K+ community members, 1.4K+ contributors
  - Peak throughput of 19.2 TiB/s
  - Awarded 2026 Databricks ISV Storage Partner of the Year
  - Expanding globally with open roles in South Korea, Saudi Arabia, France, and across the US

## Competitive Advantages
- **Unmatched performance**: Sub-10ms latency and ability to saturate any hardware (drive IOPS to network throughput)
- **Limitless scalability**: Single flat namespace scales across clusters, data centers, and clouds to exabyte level
- **Enterprise-grade reliability**: 11 nines durability, self-healing, zero-touch operations
- **Ecosystem integration**: Native support for PyTorch, Iceberg, and all major AI frameworks; richest S3 API support
- **Cost efficiency**: 40% lower total cost of ownership compared to legacy storage

## Strategic Focus
- Accelerating AI transformation with a data foundation that unifies edge, core, and cloud environments
- Enabling zero-copy hybrid data architectures for analytics and agentic computing
- Deepening partnerships with AI/ML platforms (e.g., Databricks, NVIDIA) and expanding into new geographies

## Why Work Here
- **Culture**: Described as “hackers” who are problem solvers, kind, and minimalist. Emphasis on empathy, open discourse, rapid prototyping, data-driven change, and going above and beyond for customers.
- **Work environment**: Remote-first, globally distributed. Offices in Redwood City, CA (hybrid for some roles).
- **Benefits**: Medical, vision, dental insurance; paid maternity and paternity leave; $25,000 basic life insurance; long-term disability; unlimited vacation plus 12 paid holidays; 401(k) with match.
- **Diversity**: Hiring focused solely on talent and qualifications, regardless of background or demographics.
- **Engineering culture**: Strong open-source community (32.9K GitHub stars), rapid prototyping, and minimal overhead in product and process.

## Sources
1. [MinIO Careers Page](https://www.min.io/careers)
2. [MinIO Official Site](https://www.min.io/)
3. [MinIO Job Board (Greenhouse)](https://job-boards.greenhouse.io/minio)
4. [MinIO About Page](https://www.minio.io/about)
5. [CB Insights Company Profile](https://www.cbinsights.com/company/minio)

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