2 months ago
Remote, IndiaStaff+
Responsibilities
- Lead customer and partner technical discovery and translate business, application, data, and infrastructure requirements into scalable AIStor architectures.
- 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.
- Serve as a subject matter expert in object storage, S3-compatible architectures, distributed systems, metadata, replication, erasure coding, security, performance tuning, and namespace design.
- Lead technical evaluations, system configurations, performance testing, interoperability validation, demonstrations, and proof-of-value engagements.
- Guide customers from evaluation through production onboarding, broader workload adoption, and long-term expansion.
- Provide guidance on Kubernetes, containers, automation, hybrid cloud, private cloud, public cloud, and edge deployment patterns.
- Collaborate with technology partners, resellers, customer teams, Product, Engineering, Sales, and Customer Engineering on complete solutions.
- Deliver architecture presentations, whiteboard sessions, workshops, demonstrations, best-practice guidance, and technical enablement.
- Support technical portions of RFPs, RFIs, RFQs, security reviews, architecture questionnaires, and competitive evaluations.
- Capture customer requirements, competitive insights, workload patterns, and integration needs to inform product and engineering roadmaps.
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 concepts 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, prioritization, and willingness to travel as needed.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field; equivalent practical experience is also considered.
Benefits
- Travel as needed to support customers, partners, field events, and internal team activities.
- Equal opportunity workplace and affirmative action employer.
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.