Field Application Engineer, AI Cloud

Bitdeer Technologies Group • San Jose, CA

2d • Onsite

About The Position

Bitdeer is seeking an experienced Field Application Engineer to lead technical due diligence on data centers for AI and GPU infrastructure deployment. The role assesses site readiness, validates usable power and cooling capacity, quantifies gaps and remediation needs, and provides go/no-go recommendations to move qualified sites toward deployment. It is a full-time position based in San Jose, California, with regular travel for on-site assessments and deployment support.

The engineer conducts remote reviews and site inspections, validates facility information and operator claims, and evaluates electrical, mechanical, cooling, networking, operational, and resilience capabilities for target GPU cluster configurations. The position produces decision-ready assessments covering achievable IT capacity, rack count, dependencies, cost estimates, schedule risks, and recommendations. It also coordinates issue resolution and remediation with operators, landlords, utilities, vendors, contractors, and internal teams, and contributes to a consistent assessment process and prioritized pipeline of qualified sites.

Requirements

• Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, or a related discipline, or equivalent practical experience.
• At least 5 years of experience in data center engineering, critical facilities, infrastructure solutions engineering, commissioning, or field applications engineering.
• Hands-on experience assessing or delivering data centers, with a record of identifying deployment blockers and driving technical issues to resolution.
• Strong working knowledge of electrical and mechanical infrastructure, including power distribution, backup systems, cooling, and the relationship between facility capacity and usable IT load.
• Ability to read electrical single-line diagrams, mechanical schematics, equipment data sheets, rack layouts, and commissioning reports.
• Understanding of AI or HPC infrastructure requirements, including high-density GPU systems, liquid cooling, and high-speed networking.
• Ability to write clear site assessment reports, compare options, estimate remediation scope, and explain technical risks and tradeoffs to business stakeholders.
• Strong professional English communication skills.
• Willingness to travel for site assessments and deployment support.

Nice To Haves

• Experience with GPU cloud, colocation, hyperscale, or HPC facilities, including high-density or liquid-cooled deployments.
• Experience with facility commissioning, integrated systems testing, capacity planning, or converting existing facilities for AI workloads.
• Familiarity with colocation agreements, service-level commitments, utility tariffs, power usage effectiveness (PUE), and total cost of ownership (TCO).
• Experience coordinating equipment vendors, data center operators, and engineering contractors across regions.

Responsibilities

• Lead remote reviews and on-site data center inspections to determine whether facilities can support target GPU cluster configurations, capacity, and schedules.
• Validate operator claims using drawings, equipment specifications, operating records, utility documentation, and commissioning evidence.
• Distinguish utility supply, total facility load, and usable IT capacity; assess available and committed capacity, rack density, and expansion constraints.
• Evaluate power distribution, UPS, backup generation, and redundancy for high-density AI workloads.
• Assess air cooling and direct-to-chip liquid cooling, including heat rejection, cooling distribution units, facility water conditions, flow and temperature, piping, and leak detection.
• Review rack space, floor loading, delivery access, cabling, carrier diversity, fiber routes, bandwidth, and latency; partner with network engineering on Ethernet and InfiniBand cluster designs.
• Review monitoring, maintenance, incident response, remote hands, physical security, and commissioning and acceptance records to identify operational and resilience gaps.
• Classify sites as ready for deployment, requiring defined upgrades, or requiring substantial development.
• Produce decision-ready site assessments documenting achievable IT capacity, rack count, dependencies, cost estimates, schedule risks, and a go/no-go recommendation.
• Resolve technical questions with operators, landlords, utilities, equipment vendors, and contractors.
• Define remediation and acceptance criteria, verify closure of critical issues, and hand development work to the appropriate team.
• Partner with AI ecosystem, cloud infrastructure, procurement, and engineering teams to build a consistent assessment process and prioritized pipeline of qualified sites.

Benefits

• Training and mentoring
• Development and learning opportunities
• Opportunities to network with industry pioneers and enthusiasts
• Opportunity to contribute directly to the digital asset and AI computing industry
• Involvement in new projects and process and system development
• Personal accountability and autonomy

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level