Field Architect

About MinIO

MinIO provides the data and memory foundation for enterprise AI, designed for the speed, scale, and economics required by AI and analytics. Its AIStor and MemKV solutions unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud environments. MinIO is trusted by 77% of the Fortune 100 for securing, persisting, and unlocking data value in AI factories, intelligent applications, and autonomous agents.

The Role of Field Architect

The Field Architect is a senior customer-facing technical position based in Riyadh, focusing on defining, validating, and guiding architectures for AI, analytics, cloud-native applications, and large-scale data platforms. This full-time role involves acting as a trusted technical advisor to customers, partners, and internal teams, translating business and application requirements into robust technical designs that deliver measurable outcomes. The Field Architect collaborates with the broader MinIO team through technical discovery, architecture design, proof-of-concept (PoC) delivery, production onboarding, performance validation, and long-term expansion.

Key Responsibilities

• Lead technical discovery with customers and partners to understand business goals, data sources, application requirements, infrastructure constraints, and success criteria.
• Design end-to-end architectures across the full data stack, including ingestion, CDC, batch and streaming pipelines, data processing, lakehouse storage, table formats, catalogs, query/analytics engines, orchestration, data quality, governance, and AI integration.
• Define and validate architectures for AI/ML training and inference, analytics, lakehouse environments, high-performance data pipelines, and modern application data services.
• 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.
• Build trusted relationships with customer technical stakeholders and guide them toward informed architecture decisions.
• Plan and conduct customer PoCs from initial scope through final technical review, including solution deployment, integration, testing, troubleshooting, and documentation.
• Partner with Customer Engineering, Product Management, and Engineering to facilitate customer transition from PoC to production and expand adoption.
• Provide technical leadership on Kubernetes, containers, automation, and deployment patterns across private, public, and hybrid cloud environments.
• Integrate data sources, ingestion/streaming tools, processing/analytics engines, AI platforms, identity systems, observability tools, and infrastructure components with customer and partner teams.
• Deliver architecture presentations, whiteboard sessions, demonstrations, workshops, and technical enablement for various audiences.
• Contribute to technical responses for RFPs and RFIs, covering the full data platform.
• Capture customer requirements, PoC findings, and field feedback to inform Product and Engineering teams.
• Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competing data platforms.

Qualifications and Experience

• Experience: 10+ years in a senior customer-facing technical role such as Field Architect, Solutions Architect, Sales Engineer, Systems Engineer, or Technical Consultant.
• Data Platform Expertise: Hands-on experience designing, integrating, and troubleshooting end-to-end data platforms, including ingestion, CDC, batch/streaming processing, lakehouse architecture, catalogs, query engines, orchestration, data quality, governance, and AI/analytics workloads.
• PoC Leadership: Demonstrated experience leading customer PoCs, including defining success criteria, deploying and integrating components, validating functionality and performance, resolving technical issues, and presenting results.
• Object Storage Knowledge: Strong understanding of object storage and S3-compatible architectures, including security, replication, data protection, performance, and scale-out design.
• Infrastructure Skills: Hands-on experience with Linux, networking, storage systems, containers, Kubernetes, and modern data center infrastructure.
• Data Stack Technologies: Practical experience with relevant data stack technologies such as Kafka, Debezium, NiFi, Spark, Flink, Trino, Starburst, Iceberg, Delta Lake, or data catalogs.
• AI/ML Environments: Experience designing or supporting AI, machine learning, analytics, lakehouse, or large-scale data pipeline environments.
• Cloud Experience: Experience with public and hybrid cloud environments, including AWS, Azure, GCP, OCI, or private cloud platforms.
• Communication: Strong verbal, written, whiteboarding, and presentation skills, with the ability to communicate with both technical and executive audiences.
• Collaboration: Ability to work collaboratively across customers, partners, Sales, Product, Engineering, and Customer Engineering teams.
• Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field; equivalent practical experience will also be considered.

Additional Requirements

• 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.