Rebellions | Singapore Citizens only | Full Time

ABOUT REBELLIONS

Rebellions builds high-performance AI systems with full-stack software natively supporting PyTorch and vLLM – familiar, open, and ready for production. Our Rebel 100™ delivers the best performance per dollar per watt, purpose-built for inference from the ground up, not retrofitted from training.

With proven commercial deployments already live across enterprises and governments, and a chiplet architecture built for the most demanding AI workloads, Rebellions is making good on a simple belief: every organization and nation should be able to own and control their AI, not just access it.

About the Job

As a Forward Deployed Engineer based in Singapore, you will be Rebellions’ primary on-the-ground technical resource for customers and partners across the region. The role emphasizes pre-sales technical leadership — running demos, scoping and executing PoVs, and translating customer requirements into deployable Rebellions solutions — with the technical depth to engage credibly with customer infrastructure and platform teams when the conversation gets specific.

Responsibilities and Opportunities

Partner with the regional sales team as the lead technical resource for customer engagements, from initial technical conversations through PoV design and execution
Build and deliver product demos, technical presentations, and benchmarking content tailored to real-world AI services such as LLM inference and vision pipelines
Design and prototype reference architectures for customer deployments on Rebellions' AI platform, including serving stack configuration, Kubernetes integration, and performance characterization
Evaluate end-to-end inference performance (throughput, latency, energy efficiency), identify system-level bottlenecks, and optimize serving and routing strategies for customer workloads
Engage customer technical teams — infrastructure leads, platform engineers, and ML practitioners — to walk through architecture decisions, deployment plans, and live troubleshooting
Create clear and concise technical documentation, integration guides, and best practices for customers and partners
Relay customer feedback to internal software and hardware engineering teams to help shape product direction and regional go-to-market strategy

Key Qualifications

Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field
Minimum 3 years in technical roles involving AI/ML systems deployment, customer engagement, or solutions engineering
Solid hands-on experience standing up Kubernetes-based AI inference stacks — orchestration, serving, and inference runtimes — for customer projects
Familiarity with modern distributed LLM inference orchestration (NVIDIA Dynamo, llm-d, vLLM disaggregated serving, or equivalent KV-cache-aware systems)
Working knowledge of Python and PyTorch
Strong presentation and storytelling skills — comfortable running demos, leading technical discussions, and walking customers through architecture and deployment plans
Strong communication and collaboration skills, with experience working across engineering, business, and strategy teams and engaging directly with customers
English fluency required

Ideal Qualifications

Prior experience in technical customer-facing roles such as Solutions Engineer, Sales Engineer, or Field Application Engineer — particularly with a pre-sales motion
Practical familiarity with GPU infrastructure (NVIDIA DGX/HGX, NVLink, InfiniBand/RoCE), networking, and storage for AI workloads
Solid understanding of hardware acceleration (NPU, GPU, edge AI chips) and practical experience with model optimization techniques such as quantization and pipelining
Experience producing technical content (blogs, documentation, whitepapers) for AI/ML practitioners
Comfortable representing the company at industry events — working trade show booths, running technical demos, and presenting at conferences
Comfortable operating with autonomy as part of a small, fast-moving regional team

Recruitment Process

To apply, submit your application directly on this page or send it to recruit@rebellions.ai
Application Review > 1st Online Interview > 2nd Interview(including a technical exercise & Culture-fit Session) > Management Interview > Final On-site Interview
The recruitment process may vary depending on the role and may be subject to change based on schedules and circumstances.
All updates regarding the process and results will be communicated individually via the email provided in your application.

Additional Information

This job posting may close earlier than the deadline if the position is filled.
If any false information is found in the application, the job offer may be revoked.
If the candidate does not meet the legal qualifications required for the position, employment may be restricted.
Veterans and individuals with disabilities will not face any disadvantage during the hiring process.
The scope of responsibilities may be adjusted based on the candidate’s overall experience and qualifications. If such changes are necessary, they will be discussed with the candidate before the final offer.
For any recruitment-related inquiries, please contact us at recruit@rebellions.ai