Forward Deployed Engineer (AI Infrastructure)

Location: Hybrid role with on-site work at the customer's office in Cambridge, UK; travel as needed.

Salary: £115k–£135k per year plus equity.

Company

hirify.global is a startup building foundational technology for performance, scalability, and resiliency challenges in large-scale AI data center clusters.

What you will do

• Own the technical delivery and production deployment of the company's software for a strategic customer.
• Work hands-on with GPU/XPU clusters, high-speed fabrics, schedulers, orchestration layers, and AI data center environments.
• Lead integrations, troubleshooting, performance tuning, root-cause analysis, upgrades, cluster expansion, and feature rollouts.
• Build runbooks, integration guides, automation, prototypes, fixes, and field tooling using Python, Bash, and APIs.
• Translate customer problems into technical requirements and collaborate with engineering on new product features.
• Support RFPs, RFIs, technical evaluations, proof-of-concept deployments, reference architectures, demos, workshops, and industry events.

Requirements

• 5+ years of hands-on infrastructure engineering experience as a 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 InfiniBand, RoCE, Ethernet, or NVLink; job scheduling; and training or inference workloads.
• Strong software problem-solving skills, including debugging complex distributed systems and writing production-quality scripts and tools in Python and Bash.
• Hands-on experience with AI infrastructure software such as Kubernetes, Slurm, Tinkerbell, Canonical MaaS, observability stacks, or infrastructure management platforms.
• Deep proficiency with Linux, containers, and APIs.
• Experience working with engineering teams to define and ship features based on field needs.
• Clear communication skills, including whiteboarding with SREs and briefing senior infrastructure leaders.
• Willingness to work on-site with the customer and travel as needed.
• Bachelor's or Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.

Nice to have

• Experience as a forward deployed or embedded engineer dedicated to a single large customer.
• Experience taking early-stage or pre-launch products into hyperscale, neocloud, or AI lab environments.
• Familiarity with inference serving and performance optimization, including KV-cache behavior, disaggregated serving, and GPU utilization analysis.
• Background with Prometheus, Grafana, OpenTelemetry, and data pipelines for infrastructure analytics.
• Experience at an AI infrastructure software vendor, GPU cloud provider, networking vendor, or hyperscaler.

Culture & Benefits

• Work alongside experienced builders and operators with a strong sense of unity and shared responsibility.
• Collaboration is grounded in trust, integrity, respect, and accountability for work quality.
• Supportive environment focused on fair treatment, professional growth, and meaningful work.
• Compensation includes equity in addition to the target base salary.