SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
MinIO is seeking a Field Architect to serve as a senior customer-facing technical leader responsible for defining, validating, and guiding architectures for AI, analytics, cloud-native applications, and large-scale data platforms. You will act as a trusted technical advisor to customers, partners, and internal teams, translating business and application requirements into robust technical designs that deliver measurable outcomes.
In this role, you will lead technical discovery with customers and partners to understand their business goals, data sources, application requirements, infrastructure constraints, and success criteria. You will design end-to-end architectures 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.
Key responsibilities include:
**Technical Leadership & Architecture:** Lead technical discovery and design end-to-end solutions. 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. Define and validate architectures for AI/ML training and inference, analytics, lakehouse environments, and high-performance data pipelines.
**Customer Engagement & PoC Delivery:** Build trusted relationships with customer technical stakeholders across data engineering, analytics, AI, infrastructure, platform, security, application, and operations teams. Plan and conduct customer proofs-of-concept from initial scope through final technical review, including defining success criteria, designing and deploying solutions, integrating data stack components, building representative use cases, running functional and performance tests, troubleshooting issues, and documenting results. Partner with Customer Engineering, Product Management, and Engineering to help customers move from PoC to production and expand adoption.
**Ecosystem, Enablement & Field Operations:** 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. Lead or contribute to technical responses for RFPs and RFIs.
**Product Intelligence & Market Expertise:** Capture customer requirements, PoC findings, integration needs, and field feedback to inform Product and Engineering priorities. Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competing data platforms to explain technical differentiation in the context of customer use cases.
**Requirements:**
- 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, 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 technology 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 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
