Forward Deployed Engineer

Function

Services

We're Hitachi Vantara, the data foundation trusted by the world's innovators. Our resilient, high-performance data infrastructure means that customers - from banks to theme parks - can focus on achieving the incredible with data.

If you've seen the Las Vegas Sphere, you've seen just one example of how we empower businesses to automate, optimize, innovate - and wow their customers. Right now, we're laying the foundation for our next wave of growth.

We're looking for people who love being part of a diverse, global team - and who get excited about making a real-world impact with data.

This role is open to candidates located in the North East region of the U.S.

We areseekinga highly skilled Forward-Deployed Engineer (FDE) with deepexpertisein data virtualization, hybrid cloud architectures, and AI-driven solution validation. This role partners directly with customers to design and prototype composable data and AI solutions thatvalidatetechnical feasibility, performance assumptions, and measurable business value across distributed data ecosystems.

The FDE role blends hands-on engineering, limited-scopeeconomic modeling, and customer-facing technical storytelling. The ideal candidate thrives in the field, integrating partner technologies, building working prototypes, and demonstrating GenAI and agentic AI outcomes using customer and industry datasets.

This role focuses on proving technical feasibility and business value through hands-on prototyping and customer facing engagements.

This role is not:

• A Professional Services delivery role responsible for production implementation
• A standard Pre-Sales or Solution Architecture role focused on product configuration
• An operational or run-state ownership role

This role partners closely with:

• Sales and Solution Architecture for opportunity shaping and technical validation
• Professional Services and Managed Services for delivery and operational handoff
• Product and Engineering teams for field feedback, validation, and learning transfer

• Design and prototype data virtualization architectures enabling unified, near real-time access to distributed data sources for validating feasibility, performance, and integration assumptions.
• Build prototype-level API-based extraction, streaming, ETL, and ELT pipelines.
• Integrate distributed query and transformation engines such as Spark, Presto, and SQL-based platforms in POV environments.
• Create reference architectures and working prototypes across AWS, Azure, GCP, private cloud, and on-premises environments.
• Perform workload and performance evaluations for compute, networking, storage, and GPU-accelerated environments.

• Execute proof-of-value engagements using customer and industry datasets.
• Build AI-driven prototypesshowcasingRAG, automation, and agentic workflows.
• Demonstrate AI feasibility using hybrid and GPU-accelerated environments.
• Translate prototype outcomes into technical and business value narratives.

• Build lightweight ROI, TCO, and cost comparison models to support POV outcomes.
• Evaluate architectural trade-offs within bounded validation efforts.
• Estimatefinancial impactof GenAI and agentic AI use cases.

• Translate business requirements into prototype-level architectures.
• Lead discovery sessions, technical workshops, and POV execution.
• Collaborate across sales, solution architecture, product, and delivery teams for handoff.

• Strong experience with data virtualization platforms such as Zetaris, Starburst, Dremio, or equivalent technologies.
• Handson exposure to modern data platforms including Databricks, Snowflake, Teradata, and cloud native data warehouses.
• Proficiency with Spark, Presto, SQL, distributed query engines, and performance optimization concepts.
• Experience building prototypelevel ETL/ELT pipelines and integration workflows.
• Knowledge of APIbased data integration patterns.
• Experience working in hybrid, multicloud, and onprem environments.
• Familiarity with enterprise infrastructure and accelerated compute platforms from vendors such as Hitachi, Cisco, Supermicro, HPE, Dell, Pure, and NVIDIA.
• Understanding of data governance, security, and access control principles.
• Comfort operating within large scale enterprise data ecosystems.

• Prior experience in forwarddeployed engineering, field engineering, or customer facing technical roles.
• Experience supporting consultative, prototypedriven, or POVled selling motions.
• Handson exposure to GenAI or agentic AI solutions in validation or demonstration contexts.
• Experience leveraging industry datasets or benchmarking frameworks.
• Strong communication skills with the ability to simplify complex technical concepts.

This role is ideal for engineers who thrive at the intersection of deep technical…