Solutions Engineer - Artificial Intelligence (AI) Practitioner
- Compensation
- Not disclosed
- Location
- Singapore, Central Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Solutions engineering
- Posted
Skills
Must have
- 10+ years of experience in technology consulting, pre-sales experience, preferably in software, data, analytics, infrastructure, artificial intelligence, or related fields.
- Strong understanding of programming and scripting languages, particularly Python.
- Experience designing and documenting enterprise technology solutions using established architecture and deployment methodologies.
- Ability to develop and demonstrate practical AI solutions that address real-world business problems.
- Strong understanding of machine learning, deep learning, generative AI, and modern AI application architectures.
- Experience working with AI infrastructure, including GPU systems, networking, storage, cloud services, or container platforms.
- Excellent presentation and communication skills, with the ability to engage technical and non-technical audiences.
- Ability to lead customer workshops, architecture discussions, demonstrations, and technical evaluations.
Nice to have
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a related field; an advanced degree is a plus.
- Experience with AI infrastructure, including GPU accelerators, high-performance networking such as InfiniBand or RoCE, and scale-out storage
- Experience with model-serving and inference frameworks such as vLLM, NVIDIA NIM, Triton Inference Server, TensorRT-LLM, or similar technologies.
- In-depth understanding of transformer-based language models and multimodal architectures.
- Experience with frameworks such as PyTorch, TensorFlow, Jupyter, and NVIDIA AI Enterprise.
- Familiarity with Kubernetes, OpenShift, containerization, MLOps, and production AI operations.
Full description
We are seeking a Solutions Engineer - Artificial Intelligence (AI) Practitioner to join our dynamic sales team. As an SE for AI Team, you will consult and drive the adoption of our AI solutions across various industries. You will work with potential clients, understand their specific needs, and provide tailored AI solutions that enhance their business operations. This role requires a deep understanding of AI technologies and expert capability to relay business and technical concepts to a diverse audience. Experience designing and documenting enterprise technology solutions using established architecture and deployment methodologies is an advantage.
Who You'll Work With
You will work within the Cloud and AI Infrastructure organization, helping customers transform their businesses through AI, data center, networking, and cloud technologies. You will collaborate with customers, partners, sales teams, product specialists, and product engineering teams to turn customer problems into deployable solutions and successful business outcomes.
Who You Are
You are energized by the rapid evolution of AI and enjoy solving complex technical and business problems. You are equally comfortable discussing model architectures with data scientists, infrastructure requirements with platform teams, and business outcomes with executives. You communicate clearly, present confidently, and use hands-on demonstrations to make complex ideas understandable.
Minimum Qualifications:
- 10+ years of experience in technology consulting, pre-sales experience, preferably in software, data, analytics, infrastructure, artificial intelligence, or related fields.
- Strong understanding of programming and scripting languages, particularly Python.
- Experience designing and documenting enterprise technology solutions using established architecture and deployment methodologies.
- Ability to develop and demonstrate practical AI solutions that address real-world business problems.
- Strong understanding of machine learning, deep learning, generative AI, and modern AI application architectures.
- Experience working with AI infrastructure, including GPU systems, networking, storage, cloud services, or container platforms.
- Excellent presentation and communication skills, with the ability to engage technical and non-technical audiences.
- Ability to lead customer workshops, architecture discussions, demonstrations, and technical evaluations.
Preferred Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a related field; an advanced degree is a plus.
- Experience with AI infrastructure, including GPU accelerators, high-performance networking such as InfiniBand or RoCE, and scale-out storage
- Experience with model-serving and inference frameworks such as vLLM, NVIDIA NIM, Triton Inference Server, TensorRT-LLM, or similar technologies.