Senior Technical Marketing Engineer

Lightbits Labs; United States; Sur place; USD 120 000 - 190 000; Plein temps

Résumé du poste

Lightbits Labs Ltd. seeks a hands-on technical marketing professional to translate deep infrastructure knowledge into commercial outcomes for Inferra.

Youll own the technical story from positioning to POVs and proofs, working with engineering to turn technical capability into compelling content and sales assets. You will collaborate with the SVP of AI Product & Business and partner with cloud providers to drive adoption.

Qualifications

• Experience in tech marketing for AI/infra environments with hands-on deployment knowledge.
• Minimum 5+ years in technology domain.
• Familiarity with NeoCloud, GPU cloud providers, or inference software.
• Ability to translate performance data into customer narratives and collateral.
• Proven ability to produce technical FAQs, decks and battle cards.

Responsabilités

• Deployment guides, reference architectures, and technical documentation for customers evaluating our products.
• Deploy and debug Kubernetes clusters to validate claims and reproduce issues.
• Identify and manage technical partnerships with cloud providers and ecosystem players.
• Translate performance data into customer-facing narratives and competitive positioning.
• Create battle cards, ROI tools, and technical FAQs for the sales team.
• Develop GTM content including blogs and website content.

Connaissances

Tech marketing experience

Kubernetes / infra tooling

AI infrastructure

Partnership development

Content creation

Sales enablement

GTM strategy

Technical storytelling

Executive collaboration

Formation

Bachelor's in CS or ECE

MBA is a plus

Description du poste

We are looking for a hands-on technical marketing professional who can translate deep infrastructure knowledge into commercial outcomes. In this role you will report to the SVP of AI Product & Business, spanning hands-on technical enablement, partnership development, and go-to-market execution of our flagship KV cache acceleration product, Inferra. You will partner closely with the engineering team (architecture, deployment, solutions) to turn technical capability into content, guides, and technical partnerships that drive adoption. You will own the technical story of Inferra from product positioning and market education through POVs, proof points, sales/channel enablement and field execution. You will work directly with prospective customers to help them successfully evaluate and implement Inferra, capture the technical and business outcomes of those deployments, and turn those learnings into compelling customer-facing content and sales assets

This position is located in Central/ Midwest, USA.

Responsibilities

• Deployment & technical enablement: Build and maintain deployment guides, reference architectures, and technical documentation for NeoCloud and Inference customers evaluating or deploying our products
• Hands-on validation: Deploy and debug Kubernetes clusters and inference stacks yourself to validate claims, reproduce customer issues, and keep collateral technically authentic.
• Partnerships: Identify, develop, and manage strong technical relationships with NeoClouds, GPU cloud providers, and ecosystem players (inference frameworks, hardware vendors) to expand product footprint
• Technical marketing content: Translate performance data (KV cache hit rates, TTFT, session density, cost-per-token) into customer-facing narratives, briefing decks, and competitive positioning
• Sales enablement: Create battle cards, ROI/pricing tools, and technical FAQs that help the sales team and partners sell the product credibility
• GTM execution: Conference demos, technical collaterals, blogs and website content.

Qualifications

• Prior Experience in the technology domain: 5+ years
• Bachelors in Computer Science or Electronics/Electrical engineering, MBA is a plus
• Experience in the AI infrastructure space, preferably at a NeoCloud, GPU cloud provider, or inference software company
• Hands-on experience deploying and operating Kubernetes clusters, including debugging real production issues
• Working knowledge of the inference stack—including KV cache, GPU memory constraints, and throughput/latency tradeoffs— enough to have a detailed technical conversation with an ML infra engineer
• Track record of applying infrastructure efficiency improvements through software stack optimization.
• Familiarity with inference serving frameworks like vLLM, SGLang, or others
• Strong business acumen: comfortable with partnership negotiation and commercializing technical products
• Excellent verbal and written communication — able to produce clear, technically accurate customer-facing content
• Startup mentality: High ownership, comfortable with ambiguity, and willing to do work above and below your core domains
• Prior technical marketing, application or solutions engineering experience in AI/ML infrastructure or AI model efficiency teams will be a plus
• Existing relationships in the NeoCloud/Inference-as-a-Service ecosystem and GPU cost/performance modeling is a plus