About the RoleWe are seeking a
Solutions Engineer to serve as the key technical partner to our Sales and Business Development teams for every Model Studio deal requiring custom solutioning. In this role, you will lead technical discovery calls, build high-impact demos and proofs-of-concept (POCs), and translate client requirements into tailored platform architectures and pricing structures.
You will work directly with prospects ranging from hands-on engineers to C-level executives, traveling regionally as deal flow demands.
Responsibilities- Technical Discovery: Partner with Sales and BD on calls to evaluate client model needs, latency tolerances, throughput requirements, and budget constraints.
- Demos & Proofs-of-Concept: Design, build, and deliver customized technical demos and POCs that showcase Model Studio's ability to solve specific client use cases.
- Architecture & Pricing Design: Translate customer requirements into proposed technical solutions and pricing structures in close collaboration with Sales and Commercial/Legal teams.
- Objection Handling: Own and resolve technical objections during the sales cycle, addressing performance/throughput benchmarks, model availability, and SLA questions.
- Deal Support: Assist in technical scoping and drafting Order Forms alongside commercial and legal stakeholders.
- Product Feedback Loop: Channel structured customer feedback (feature gaps, competitive intelligence, pricing friction) directly to the Product team.
- Sales Enablement: Create reusable technical sales assets, including reference architectures, demo scripts, benchmark decks, and FAQ playbooks.
- Post-Sale Handoff: Provide light post-sale onboarding support to ensure a seamless transition to Operations and Customer Success.
Requirements- Experience: 5-8 years in a customer-facing technical role (Solutions Engineer, Solutions Architect, Sales Engineer, or Technical Pre-Sales), ideally within an AI/ML infrastructure or cloud enterprise company.
- Domain Knowledge: Solid working knowledge of LLM inference concepts, including latency vs. throughput tradeoffs, GPU vs. token-based pricing, and modern model serving architectures.
- Presentation Skills: Exceptional ability to run live technical demos and think on your feet in front of technical teams and C-suite stakeholders.
- Communication: Excellent written and verbal communication skills in English.
- Education: Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
- Travel: Willingness to travel to client sites and regional offices as deals require.
Nice-to-Haves / Preferred Qualifications- Direct experience selling or supporting Model-as-a-Service (MaaS) or inference API products.
- Familiarity with the open-source LLM ecosystem (Hugging Face, vLLM, common inference frameworks) and licensing considerations.
- Prior experience partnering directly with Product organizations on technical scoping and roadmap alignment.
- Languages: Professional fluency in Mandarin is a strong plus to support regional client coverage.
