Senior Technical Marketing Engineer

Lightbits Labs; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

Lightbits Labs in the Central/Midwest, USA seeks a hands-on Senior Technical Marketing Engineer to translate deep infrastructure knowledge into commercial outcomes. 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 own the technical story of Inferra from positioning and market education through POVs, proof points, sales/channel enablement

Qualifications

• 5+ years in technology domain.
• Bachelor's in CS or Electronics/Electrical engineering; MBA is a plus.
• Experience in AI infrastructure space (NeoCloud, GPU cloud or inference software).
• Hands-on Kubernetes deployment and production debugging.
• Understanding of inference stack, KV cache, GPU memory and throughput/latency tradeoffs.
• Familiarity with inference serving frameworks like vLLM or SGLang.
• Strong business acumen for partnerships and commercialization.
• Excellent verbal and written communication for customer-facing content.
• Startup mindset with ownership and comfort with ambiguity.
• Prior technical marketing/solutions engineering in AI infra is a plus.
• Existing relationships in NeoCloud/Inference ecosystem and GPU cost/perf modeling are a plus.

Responsibilities

• Deployment & technical enablement: Build deployment guides and reference architectures for NeoCloud and Inference customers.
• Hands-on validation: Deploy and debug Kubernetes clusters and inference stacks to validate claims.
• Partnerships: Develop technical relationships with NeoClouds, GPU providers, and ecosystem players.
• Technical marketing content: Translate performance data into customer-facing narratives and decks.
• Sales enablement: Create battle cards, ROI/pricing tools, and technical FAQs.
• Community engagement: Contribute to GitHub, Hugging Face, vLLM/SGLang communities.
• GTM execution: Conference demos, technical collateral, blogs and website content.

Skills

Deployment

Kubernetes

AI infrastructure

Partnerships

Content creation

Sales enablement

Community engagement

GTM execution

Education

Bachelor's in Computer Science or Electronics/Electrical Engineering

MBA is a plus

Tools

Kubernetes

vLLM

SGLang

Job description

Title : Senior Technical marketing engineer

Location : Central/ Midwest, USA

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

Title : Senior Technical marketing engineer

Location : Central/ Midwest, USA

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

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
• Community engagement: Contribute to technical community engagement (GitHub, Hugging Face, vLLM/SGLang communities)
• 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