Field Application Engineer

Responsibilities

• Lead technical pre‑sales engagements for Nonstop AI™ software products
• Drive early‑access and production deployments
• Provide hands‑on post‑sales support for customers running Delos Nonstop AI™ in production
• Partner with sales and marketing team to lead technical discovery, solution design, and product demonstrations of Delos Data’s AI infrastructure software
• Own proof‑of‑concept, early‑access, pilot and production deployments end‑to‑end: scoping, success criteria, execution, and conversion to production
• Develop and deliver technical presentations, architecture proposals, and competitive evaluations for engineering and executive audiences
• Respond to RFPs/RFIs and build the technical justification that supports customer purchase decisions
• Provide hands‑on post‑sales support for production deployments, including integration, troubleshooting, performance tuning, and escalation management
• Guide customers through software upgrades, cluster expansion, and new feature adoption
• Develop runbooks, integration guides, and best‑practice documentation tailored to customer environments
• Serve as the technical escalation point between customer operations teams and Delos’ engineering
• Build and maintain deep technical relationships with infrastructure, SRE, and platform engineering teams at hyperscale, neocloud, and AI labs customers
• Navigate the unique requirements of these environments: multi‑tenancy, custom hardware fleets, extreme scale, strict SLAs, and bespoke integration needs
• Align customer deployment milestones and operational needs with Delos product release cycles
• Channel structured field feedback for feature gaps, bugs, competitive intelligence into product and engineering
• Build demo environments, reference architectures, and technical collateral for the sales organization
• Represent Delos Data at industry events, customer briefings, and technical workshops

• 5+ years in a customer‑facing technical role (FAE, sales engineer, solutions architect, or TAM) for infrastructure software
• Proven experience supporting or selling AI infrastructure software spanning orchestration, telemetry, analytics, and management — e.g., Kubernetes, Slurm, Tinkerbell, Canonical MaaS, observability stacks, or infrastructure management platforms
• Direct experience working with hyperscalers, neoclouds, AI labs as customers, with an understanding of their procurement processes, technical expectations, and operational scale
• Strong working knowledge of AI compute environments: GPU/XPU clusters, high‑speed interconnects (Infini Band/RoCE/Ethernet/NVLink), job scheduling, and inference/training workloads
• Hands‑on proficiency with Linux, containers, APIs, and scripting (Python, Bash) for demos, integrations, and troubleshooting
• Excellent communication skills — able to whiteboard cluster architecture with SREs and brief senior infrastructure leaders with clarity
• Willingness to travel to customer sites and industry events as needed (typically 25–40%)