AI / LLM Deployment Engineer

Sourcing Must Haves

• Ideally 10+ years in software engineering/infrastructure, including 5+ years deploying AI/LLM models into production environments.

• Proven experience deploying AI/LLM models in on-premise, air-gapped, sovereign environments

• Expertise with LLM deployment runtimes such as vLLM, TGI, Ollama or equivalents

• GPU cluster management experience (NVIDIA H100/H200, NVLink topology, InfiniBand networking)

• Experience applying quantization techniques (GPTQ, AWQ, GGUF) in production

• Kubernetes-based model serving at scale

• Familiarity with open-weight models (Kimi, DeepSeek, Qwen, LLaMA family)

• Ability to design and implement deployment architecture for secure, air-gapped environments

Sourcing Nice to Haves

• Background in high-performance computing or distributed systems beyond AI workloads

• Experience deploying models for government, intelligence, or other highly regulated sectors

• Familiarity with FIPS-compliant environments and secure model packaging

• Experience with model fine-tuning pipelines and LoRA adapter management

• Prior work in vulnerability management or secure enterprise software environments

Location & Working Pattern

• Initially fully remote with willingness to travel to Abu Dhabi as needed

• Long-term relocation to Abu Dhabi welcomed but not mandatory

• Candidates should ideally work close to Gulf Standard Time to reduce time zone challenges

Other Preferences

• Strong technical alignment prioritized over perfect fit; candidates meeting ~50-75% of profile encouraged

• Candidate quality significantly more important than quantity

• Confidential role; applications via referral or selected agencies only

• Salary flexible; client willing to exceed budget for exceptional candidates