AI Engineer – Series A start-up

Join this rapidly scaling AI-native Fintech start-up that’s already raised a significant Series A and is now building its core AI engineering team.

This is a career-defining role, and given the NOISE in the AI job market right now, this is the AI start-up to pay attention to – it could be one of the best career decisions you make.

The company is building production-grade agentic AI systems for complex, high-stakes enterprise workflows. No demos. No theatre. Real customers, real usage, real pressure.

Engineers work shoulder to shoulder with highly successful entrepreneurs every day. There are no layers, no hand-offs, and no slow approvals. The intensity is intentional—it’s about learning faster, shipping faster, and taking ownership much earlier than most roles allow.

On the work itself: you’ll own large parts of the agentic AI infrastructure end-to-end. That means designing and deploying multi-agent systems, building RAG pipelines, creating evaluation frameworks that actually measure quality and safety, and shipping AI features used by real enterprise customers. You’ll build backend services and APIs (Python, FastAPI/Django), work across infrastructure and deployment pipelines, and ensure everything holds up in production.

You won’t be endlessly tuning prompts or churning out throwaway PoCs. This is about owning systems, not slides.

They’re looking for strong software engineers who’ve already put AI systems into production, are comfortable across backend, data, and infrastructure, and don’t flinch when priorities shift. Ambiguity is part of the job. So is growth.

Exceptional engineers choose environments like this because the talent density raises their bar, founder access is direct and unfiltered, and a single year here can compress several years of learning elsewhere.

They’re aggressively hiring an elite team of Applied AI engineers, so now is the time to join at this inflexion point – huge funding round just raised, requirement to scale at a ferocious pace = RAPID career growth for you.

If reading this feels both intimidating and exciting—that’s usually the right signal!

Experience required

• Educated to at least degree level in a relevant subject; Mathematics, Statistics, Machine Learning, Engineering, Science etc.
• 4+ years in AI/ML engineering with a foundation in software engineering OR a recent move from pure software engineering into Agentic AI.
• Hands-on experience building and deploying LLM/agentic systems into production.
• Strong software engineering foundations: orchestration, memory, deployment, and monitoring is ESSENTIAL.
• Familiarity with agentic frameworks (LangGraph, ReAct, CoT loops) and/or proven ability to build without them.
• Knowledge of PyTorch/TensorFlow, RAG, vector databases, and orchestration tools.
• Background in start-ups (hands-on generalists) or consultancies (client exposure).
• Experience in regulated industries (finance, healthcare, public sector) a plus
• Independent, entrepreneurial mindset; thrives without hand-holding.

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