2 months ago
Base Salary
$200k - $225k/yr
Responsibilities
- Lead customer and partner technical discovery and define scalable AIStor architectures aligned to business and application requirements.
- Design and validate architectures for AI/ML training and inference, analytics, data lakehouse environments, high-performance pipelines, large object workloads, and modern application data services.
- Advise customers on object storage, S3-compatible architectures, distributed systems, metadata, replication, erasure coding, security, performance tuning, and large-scale namespace design.
- Lead technical evaluations, system configurations, performance testing, interoperability validation, demonstrations, and proof-of-value engagements.
- Guide customers from evaluation through production deployment and broader adoption across workloads, teams, and use cases.
- Provide technical leadership on Kubernetes, containers, automation, hybrid cloud, private cloud, public cloud, and edge deployment patterns.
- Collaborate with technology partners, resellers, and customer teams on integrated solutions involving analytics, AI, Kubernetes, data protection, identity, observability, and public cloud services.
- Deliver architecture presentations, whiteboard sessions, workshops, demonstrations, and technical enablement for customers, partners, and internal teams.
- Lead or support technical responses for RFPs, RFIs, RFQs, security reviews, architecture questionnaires, and competitive evaluations.
- Capture customer requirements, competitive insights, workload patterns, integration needs, and product feedback for Product and Engineering teams.
- Travel as needed for customers, partners, field events, and internal team activities.
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.
- Strong background in enterprise storage, object storage, distributed systems, cloud infrastructure, data platforms, or high-performance data-intensive applications.
- Strong understanding of object storage and S3-compatible architectures, including HTTP, REST APIs, JSON, security models, replication, data protection, and scale-out system design.
- Hands-on experience with Linux, networking, storage systems, virtualization, containers, Kubernetes, and modern data center infrastructure.
- Experience designing or supporting AI, machine learning, analytics, data lakehouse, or large-scale data pipeline environments.
- Familiarity with Databricks, Starburst, Spark, Trino, Iceberg, Delta Lake, Kafka, PyTorch, TensorFlow, or other AI and analytics frameworks is preferred.
- Experience with public and hybrid cloud environments, including AWS, Azure, GCP, OCI, or private cloud platforms.
- Ability to conduct technical discovery, design architectures, build demonstrations, guide proof-of-value execution, analyze performance, and communicate tradeoffs clearly.
- Ability to work across heterogeneous enterprise environments involving compute, storage, networking, security, identity, observability, backup, disaster recovery, and application teams.
- Strong verbal, written, whiteboarding, and presentation skills for technical and executive audiences.
- Ability to collaborate across customers, partners, Sales, Product, Engineering, and Customer Engineering teams.
- Strong customer-success orientation, intellectual curiosity, ownership, and prioritization skills.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
Benefits
- Medical, dental, and vision health care plan.
- 401(k) with a 3% contribution.
- Pre-IPO stock options.
- At least 12 public holidays.
- Flexible time off.
- Travel as needed is expected to support customers, partners, field events, and internal team activities.
Tech Stack
Categories
Solutions Engineering
About MinIO
MinIO builds high-performance, S3-compatible object storage and related data systems for enterprises running data lakes, analytics, and AI across on‑prem, edge, and cloud environments. It monetizes through enterprise subscriptions and support on top of its open-source software, and offers products such as AIStor and MemKV for AI and memory-centric workloads. Founded in 2014 and headquartered in Redwood City, California, it is privately held.