25 days ago
Remote, United StatesStaff+
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
