Artificial Intelligence Engineer
You will build and ship ML/LLM systems, implementing model development, fine-tuning, deployment, data pipelines, and evaluation frameworks, and work with agentic architectures. The role is with a stealth portfolio company backed by a leading VC firm.
Free Tailor for ATS: 10/10 runs left
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 opening a small number of confidential conversations now with strong engineers, so we can move quickly once the mandate is formally released.
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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