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Delos Data

Forward Deployed Engineer

Cambridge Posted today

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No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

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About the role

Forward Deployed Engineer - AI About us We are a startup building foundational technology to address performance, scalability, and resiliency challenges in large-scale AI data center clusters. We are backed by top-tier VC firms and notable angel investors. The company is led by experienced builders and operators who have founded companies, taken them to scale, and exited successfully. We work with a strong sense of unity and shared responsibility, and we expect trust, integrity, and respect in how we collaborate and make decisions. We hold ourselves accountable to one another and to the quality of the work we deliver. Headquartered in Silicon Valley, we operate across a mix of remote and on-site locations in the U.S., Canada, and the U.K. We aim to create an environment where people are treated fairly, supported in their growth, and are empowered to do meaningful work alongside others who take the craft seriously. Some Recent Press: https://www.reuters.com/business/delos-data-chip-startup-founded-by-intel-veterans-raises-100-million-ai-networks-2026-09-15/ We are looking for: We are looking for a talented Forward Deployed Engineer to be embedded with one of our strategic customers running our software in production. In this role, you will work hands-on inside the customer's AI data center environment, solving hard deployment and operational problems and turning what you learn into new product features alongside our engineering team. While most of your time will go to this customer, you will also bring your field experience to future customer pursuits, contributing hands-on to RFPs, technical evaluations, and new deployments. We are looking for a "builder" who has built and run AI infrastructure at scale, ideally at a neocloud or frontier AI lab, and who thrives on solving real problems in production. Key Responsibilities • Serve as the dedicated technical owner for a strategic customer's production deployment of our software. • Work hands-on in the customer's AI data center environment, including GPU/XPU clusters, high-speed fabrics, schedulers, and orchestration layers. • Lead integration, troubleshooting, performance tuning, and root-cause analysis for production issues. • Guide the customer through software upgrades, cluster expansion, and new feature rollouts. • Build runbooks, integration guides, and automation tailored to the customer's environment. • Build deep working relationships with the customer's infrastructure, SRE, and platform engineering teams. • Turn customer problems into clear technical requirements and work with our engineering team to design and deliver new features. • Write and test code (Python, Bash, APIs) to prototype fixes, integrations, and tooling in the field. • Feed structured insights on bugs, feature gaps, and competitive needs back into product and engineering, and align customer milestones with our product release cycles. • Contribute hands-on technical work to RFPs, RFIs, technical evaluations, and proof-of-concept deployments for new customers. • Help build reference architectures, demo environments, and technical collateral, and represent the company at customer briefings, technical workshops, and industry events as needed. Required Skills and Qualifications • 5+ years in a hands-on infrastructure engineering role (forward deployed engineer, SRE, platform engineer, solutions architect, or similar) with direct customer or internal-customer exposure. • Proven AI data center experience: deploying and operating GPU/XPU clusters with high-speed interconnects (InfiniBand/RoCE/Ethernet/NVLink), job scheduling, and training/inference workloads. • Strong software problem-solving skills, including debugging complex distributed systems and writing production-quality scripts and tools in Py

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