Field Architect
No salary listed
Expert
Bachelor's
Riyadh Saudi Arabia
RemoteTravel as needed to support customers, partners, field events, and internal team activities.
Solution EngineeringImplementation & Technical Account Management
About the job
Requirements
- At least 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, including several of ingestion, change data capture, batch and streaming processing, lakehouse architecture, catalogs, query engines, orchestration, data quality, governance, and AI or analytics workloads.
- Demonstrated experience leading customer proofs of concept, 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, including communicating with 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 is also considered.
Responsibilities
- Lead technical discovery with customers and partners to understand business goals, data sources, application requirements, infrastructure constraints, and success criteria, and design end-to-end architectures that address those requirements.
- Design solutions across the full data stack, including ingestion and change data capture, batch and streaming pipelines, data processing, lakehouse storage and table formats, catalogs, query and analytics engines, orchestration, data quality, governance, and AI integration; guide customers through architecture decisions and tradeoffs.
- Define and validate architectures for AI and machine-learning 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 across data engineering, analytics, AI, infrastructure, platform, security, application, and operations teams, and guide them toward informed architecture decisions.
- Plan and conduct customer proofs of concept from initial scope through final technical review; agree on success criteria, design and deploy solutions, integrate required data stack components, build representative use cases, run functional and performance tests, troubleshoot issues, document results, and drive each proof of concept to a clear outcome and production plan.
- Partner with Customer Engineering, Product Management, and Engineering to help customers move from proof of concept to production and expand adoption across additional workloads and teams.
- Provide technical leadership on Kubernetes, containers, automation, and deployment patterns across private, public, and hybrid cloud environments.
- 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.
- Deliver architecture presentations, whiteboard sessions, demonstrations, workshops, and technical enablement for customers, partners, and internal teams.
- Lead or contribute to technical responses to requests for proposals and requests for information, covering architecture, integrations, security, scalability, performance, and operational requirements across the data platform.
- Capture customer requirements, proof-of-concept findings, integration needs, and field feedback; work with Product and Engineering teams to resolve gaps and inform priorities.
- Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competing data platforms, and explain technical differentiation in the context of customer use cases.
About the company
MinIO provides high-performance, S3-compatible object storage designed for large-scale workloads in AI, machine learning, data lakes, and databases. It delivers a software-defined storage solution that can run on any cloud or on-premises infrastructure, offering encryption, data protection, governance, and immutable storage with active-active, multi-site replication for mission-critical environments. It differentiates itself through a dual-licensing model (open-source GNU AGPL v3 plus a commercial enterprise license), enabling both free use and paid enterprise features and support. Its goal is to give organizations a secure, scalable, and flexible object storage platform that works across heterogeneous infrastructure and meets regulated workloads.
Company Size
201-500
Company Stage
Series B
Total Funding
$146.3M
Headquarters
Palo Alto, California
Founded
2014
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Simplify's Take
What believers are saying
- Databricks recognized MinIO in June 2026, validating hybrid AI data demand.
- AIStor Tables launched globally in February 2026, with claimed up to 40% lower storage costs.
- HUMAIN selected MinIO in 2026 for sovereign AI infrastructure across Saudi Arabia and beyond.
What critics are saying
- MinIO archived its community repository on April 25, 2026, killing upstream OSS momentum.
- Community binaries stopped in 2025, forcing operators to build frozen source themselves.
- Forks like Silo already target displaced users; large churn could hit enterprise conversions by 2027.
What makes MinIO unique
- AIStor Tables embeds Apache Iceberg V3 directly into storage, unlike AWS S3 Tables.
- MinIO won Databricks 2026 ISV Storage Partner of the Year for zero-copy hybrid access.
- MemKV and AIStor Memory extend MinIO from object storage into AI context infrastructure.
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Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- 401(k) Company Match
- Pre-IPO Stock Options
- Paid Holidays
- Flexible Time Off