Space Executive

Space Executive is partnering with one of the country's leading VC firms, who is giving us early visibility into an AI Engineer search across their Data & AI stealth portfolio. We're currently hiring for a recent Series B start-up, focusing on a highly regulated industry.

If you're an AI Engineer with hands-on experience building and shipping ML/LLM systems in production, we'd like to hear from you. Beyond this specific search, we work closely with several VC firms across their wider portfolios, so we're always happy to have a broader conversation about what's out there if the timing or fit isn't quite right here.

What You'll Own

• Model Development & Integration - Build, fine-tune, and deploy ML/LLM systems that sit at the core of the product, not bolted on as a feature
• Production ML Infrastructure - Own the pipelines, serving layer, and evaluation harnesses that take a model from notebook to production
• Data Pipeline Design - Build and maintain the data infrastructure that feeds training and inference; quality and latency both matter
• Applied Research - Stay close to the latest techniques (RAG, fine-tuning, agentic workflows) and bring back what's actually useful, not just novel
• Cross-Functional Partnership - Work directly with product and founders to translate ambiguous problems into shippable ML features
• Hands-On at Every Stage - Comfortable moving between experimentation, infra work, and production debugging; this isn't a research-only seat

Who You Are

• Strong hands-on engineering background; you've shipped ML/AI systems into production, not just built prototypes
• Experience with modern LLM tooling; fine-tuning, RAG, evaluation frameworks, or agentic architectures
• Comfortable operating at a startup or scale-up where the infrastructure and process don't fully exist yet
• Confident working directly with founders and product leads; can explain technical tradeoffs without over-engineering the conversation
• Comfortable operating under NDA during a stealth phase before the company's identity or product is public

Why This Role

Strong early signal, funding in place, and a technical build-out that's happening now, not in six months. Getting in early means shaping the ML architecture and team from a foundational stage, not inheriting someone else's decisions.

Interested, or want to talk more broadly about opportunities across our VC network? Reach out to register your interest confidentially.

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