MinIO

S3-compatible object storage for AI workloads

Field Architect

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours

Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

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; experience with HTTP, REST APIs, JSON, security models, replication, data protection, and scale-out system design is highly valuable.
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 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.
Experience with public cloud 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.
Comfort working with heterogeneous enterprise environments involving compute, storage, networking, security, identity, observability, backup, disaster recovery, and application teams.
Strong verbal, written, whiteboarding, and presentation skills, with the ability to communicate complex technical concepts to technical and executive audiences.
Ability to work collaboratively across customers, partners, Sales, Product, Engineering, and Customer Engineering teams.
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, application requirements, data architecture, infrastructure constraints, and success criteria, then define scalable AIStor architectures mapped to those requirements.
Define and validate AIStor architectures for AI and machine learning training and inference, analytics platforms, data lakehouse environments, high-performance data 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 large-scale namespace design.
Build trusted relationships with customer technical stakeholders and guide informed architecture decisions, proactively identifying opportunities to improve performance, resilience, scale, and operational efficiency.
Lead technical evaluations, system configurations, performance testing, interoperability validation, and proof-of-value engagements in customer environments.
Partner with Customer Engineering, Product Management, and Engineering to help customers move from evaluation to production and expand adoption across workloads, teams, and use cases.
Provide technical leadership on Kubernetes, containers, automation, and cloud-native deployment patterns, including hybrid cloud, private cloud, public cloud, and edge infrastructure models.
Collaborate with technology partners, reseller partners, and customer teams to support integrated solutions involving analytics engines, AI platforms, Kubernetes distributions, data protection tools, identity systems, observability platforms, and public cloud services.
Build and deliver architecture presentations, whiteboard sessions, demonstrations, best practices, workshops, and technical enablement sessions for customers, partners, and internal teams.
Contribute to or lead technical portions of RFPs, RFIs, RFQs, security reviews, architecture questionnaires, and competitive evaluations.
Capture field feedback, competitive insights, workload patterns, integration needs, and enhancement opportunities, and work with Product and Engineering teams to inform roadmap priorities and improve customer outcomes.
Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competitive storage trends, and help internal teams and customers understand AIStor’s differentiation.

Desired Qualifications

Familiarity with ecosystem technologies such as Databricks, Starburst, Spark, Trino, Iceberg, Delta Lake, Kafka, PyTorch, TensorFlow, or other AI and analytics frameworks.

MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data.

The Field Architect role at MinIO is a senior customer-facing technical leadership position focused on defining, validating, and guiding AIStor architectures for AI, analytics, cloud-native applications, and large-scale data infrastructure. You will serve as a trusted technical advisor to customers, partners, and internal teams, translating business and application requirements into robust technical designs that deliver measurable outcomes.

You will collaborate closely with the broader MinIO team to ensure customers are successful through technical discovery, architecture design, proof-of-value execution, production onboarding, performance validation, and long-term expansion. Success in this role requires deep technical curiosity, hands-on architecture skills, strong communication, and the ability to connect AIStor’s capabilities to the data-intensive workloads that matter most to our customers.

What You Will Do:

Technical Leadership & Architecture

Technical Architecture and Discovery: Lead technical discovery with customers and partners to understand their business goals, application requirements, data architecture, infrastructure constraints, and success criteria. Define scalable AIStor architectures that map directly to those requirements.
AI and Analytics Workload Design: Define and validate AIStor architectures for AI/ML training and inference, analytics platforms, data lakehouse environments, high-performance data pipelines, large object workloads, and modern application data services.
Object Storage and S3 Expertise: Serve as a subject matter expert in object storage, S3-compatible architectures, distributed systems, metadata, replication, erasure coding, security, performance tuning, and large-scale namespace design.

Customer Engagement & Advisory

Customer Technical Advisor: Build trusted relationships with customer technical stakeholders, including infrastructure, platform, analytics, AI, security, application, and operations teams. Guide customers toward informed architecture decisions and proactively identify opportunities to improve performance, resilience, scale, and operational efficiency.
Proof-of-Value Execution: Lead technical evaluations, system configurations, performance testing, interoperability validation, and proof-of-value engagements that demonstrate AIStor’s value in real customer environments.
Customer Success Beyond the Win: Partner with Customer Engineering, Product Management, and Engineering teams to help customers move from evaluation to production and from initial deployment to broader adoption across additional workloads, teams, and use cases.

Ecosystem, Enablement & Field Operations

Cloud-Native and Kubernetes Guidance: Provide technical leadership on Kubernetes, containers, automation, and cloud-native deployment patterns, including hybrid cloud, private cloud, public cloud, and edge infrastructure models.
Solution Integration and Ecosystem Collaboration: Work with technology partners, reseller partners, and customer teams to support complete solutions involving analytics engines, AI platforms, Kubernetes distributions, data protection tools, identity systems, observability platforms, and public cloud services.
Technical Presentations and Enablement: Build and deliver compelling architecture presentations, whiteboard sessions, demonstrations, best practices, workshops, and technical enablement sessions for customers, partners, and internal teams.
RFP, RFI, and Technical Response Support: Contribute to or lead technical portions of RFPs, RFIs, RFQs, security reviews, architecture questionnaires, and competitive evaluations.

Product Intelligence & Market Expertise

Product and Engineering Feedback: Advocate for customer requirements internally by capturing field feedback, competitive insights, workload patterns, integration needs, and enhancement opportunities. Work with Product and Engineering teams to help inform roadmap priorities and improve customer outcomes.
Competitive and Market Expertise: Stay current on object storage, data lakehouse, AI infrastructure, analytics, Kubernetes, cloud, and competitive storage trends. Help internal teams and customers understand where AIStor is differentiated.

Your Skills and Experience:

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; experience with HTTP, REST APIs, JSON, security models, replication, data protection, and scale-out system design is highly valuable.
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 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 ecosystem technologies such as Databricks, Starburst, Spark, Trino, Iceberg, Delta Lake, Kafka, PyTorch, TensorFlow, or other AI and analytics frameworks is a strong plus.
Experience with public cloud 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.
Comfortable working with heterogeneous enterprise environments involving compute, storage, networking, security, identity, observability, backup, disaster recovery, and application teams.
Strong verbal, written, whiteboarding, and presentation skills, with the ability to communicate complex technical concepts to 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.

Equal Opportunity Policy (EEO)

MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

About the Company

MinIO

S3-compatible object storage for AI workloads

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, CA
Founded: 2014

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