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.
