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- 2時間前
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- Eligibility
- Experienced professionals with a background in solutions architecture, sales engineering, implementation consulting, or similar partner/customer-facing technical roles can apply.
- Resume
- Required to apply
Where you'll work
仕事内容
Role overview
We are hiring a Mid/Senior Solutions Architect in Qatar to join a pre-sales function and help translate customer needs into practical, scalable, and resilient AI-driven solutions.
What you will do
- Work closely with prospective customers and partners in a consultative, customer-facing pre-sales environment.
- Prepare technical responses for proposals, tenders, and RFPs.
- Deliver product demonstrations independently and tailor them to both technical and non-technical audiences.
- Design AI/ML solution architectures across cloud, on-premise, sovereign, and hybrid environments.
- Advise on deployment, orchestration, monitoring, and CI/CD practices for ML operations.
- Support infrastructure planning for LLM workloads, including GPU sizing and performance evaluation.
- Contribute code in Python and SQL when needed for solution design or validation.
Must-have expertise
- Background in solutions architecture, sales engineering, implementation consulting, or a similar partner-facing technical role.
- Strong verbal and written communication skills with the ability to present to varied stakeholders.
- Working knowledge of AWS, Azure, and GCP, along with services such as SageMaker, Vertex AI, and AzureML.
- Practical experience with MLOps tools and workflows, including CI/CD, monitoring, Kubeflow, Flyte, and MLflow.
- Comfort using Docker and Kubernetes to package and deploy AI workloads.
- Understanding of LLM inference stacks such as vLLM, llama.cpp, and OpenVINO, plus formats like ONNX, .safetensors, and HuggingFace model hub assets.
- Experience estimating GPU needs for inference or training, from A10 through H200 class hardware.
- Ability to assess LLM quality and performance using metrics such as accuracy, latency, and throughput.
- Hands-on familiarity with Python, SQL, PyTorch, TensorFlow, and Hugging Face libraries/frameworks.
Preferred exposure
- Computer vision, speech, and vision-language model experience.
- Model optimization, quantization, or deployment on edge devices.
- Designing retrieval-augmented generation pipelines or multi-agent systems.
- Building batch and streaming data architectures and working with big data platforms.
- Awareness of data privacy, responsible AI, GDPR, and relevant national AI regulations.