Artificial Intelligence Engineer

💎 Equity with real upside — not just paper value 💎 💲 ~$160k equity over 4 years This is an opportunity to join a fast-scaling, AI-native fintech that has just secured a major Series A and is now assembling a world-class AI engineering team. Let’s be blunt — the AI market is crowded with noise right now. This isn’t one of those roles. This is a business building real systems, with real users, solving real enterprise problems. They are developing production-grade agentic AI platforms designed for complex, high-value workflows in enterprise environments. You’ll work directly with founders, senior leadership, and a highly selective group of engineers. No bureaucracy, no endless approvals, just high ownership, rapid iteration, and a genuine expectation to ship. This opportunity offers accelerated learning , early ownership, and exposure most engineers don’t get until much later in their careers. Top engineers are drawn to environments like this for a reason: ✅High talent density ✅Direct Founder Access ✅The kind of pace where 12 months here can equal 3+ years elsewhere. What you’ll actually be doing You’ll take ownership of core parts of the agentic AI stack end-to-end, including: Designing and deploying multi-agent systems Building and scaling RAG-based architectures Developing evaluation frameworks focused on performance, reliability, and safety Delivering AI-powered features used by enterprise clients in production You’ll also be hands‑on with backend engineering (Python, FastAPI/Django), infrastructure, and deployment, making sure systems are robust, scalable, and production‑ready. With fresh funding secured and aggressive growth plans, this is a genuine inflection point and a chance to fast‑track your career in a meaningful way. Experience Required Educated to at least degree level in a relevant field (Maths, Stats, ML, Engineering, etc.) 4+ years in AI/ML engineering, or strong software engineering background with a move into AI Proven experience deploying LLM or agent‑based systems into production Solid engineering fundamentals across orchestration, memory, deployment, and monitoring Experience with tools/frameworks like LangGraph, ReAct, CoT — or ability to build systems from first principles Familiarity with PyTorch/TensorFlow, RAG pipelines, vector DBs, and modern infra Background in startups (builders) or consultancies (client‑facing delivery) Self‑directed, adaptable, and comfortable operating in ambiguity #AgenticAI #AIJobs #SoftwareEngineeringjobs #J-18808-Ljbffr