🚀 Applied AI Engineer 🚀
✨Famous Founders ✨
The AI start-up that WILL succeed - the equity you WILL realise
đź“Ť Manhattan, New York (5 days per week, in-office)
đź’¸ Highly competitive
🧩 $160k vested over 4 years (annual vesting)
🚨 This Is Not a Lifestyle Role. It is a career-defining one.
This role sits inside a fast-growing, AI-native company building production-grade agentic systems for complex, high-stakes enterprise workflows. The business has scaled at exceptional speed, closed a major Series A, and is now focused on building a small, elite engineering team to own the core AI infrastructure end-to-end .
đź’Ş The Environment
- 12 hours a day, 5 days a week, in the office
- Exceptional, high-performing teams
- Engineers work directly with founders daily
- No layers, no slow approvals, no hand-offs
The intensity is deliberate. The aim is compression:
- Faster learning curves
- Faster iteration cycles
- Faster ownership and decision-making
If you want flexibility, this isn’t the role.
If you want to become exceptional very quickly, it might be the best move of your career.
🧩 What You’ll Actually Be Building
You will own and drive large portions of the AI agent infrastructure, from design through to production deployment.
This includes:
- Designing and deploying multi-agent systems
- Building and integrating RAG pipelines
- Creating evaluation frameworks (evals) to measure accuracy, reliability, and safety
- Shipping AI-powered features used by real enterprise customers
- Building backend services and APIs (Python, Django / FastAPI preferred)
- Working across the stack — APIs, databases, infrastructure, and deployment pipelines
- Ensuring systems are scalable, performant, and secure in production
You’ll also:
- Build data pipelines for model training and continuous improvement
- Work with cloud infrastructure, containers, and CI/CD
- Collaborate directly with founders, designers, and growth teams
- Mentor junior engineers and raise the technical bar across the team
You will not be:
- Tuning prompts endlessly
- Producing throwaway PoCs
- Working on slideware or “AI demos”
🧠Who This Is For
You’ll likely have:
- Foundational software engineering experience
- Hands-on experience designing and deploying AI systems into production, end-to-end
- Strong backend engineering skills (Python)
- Experience with relational databases, Redis, task queues, and background workers
- Familiarity with Docker, Kubernetes, and modern cloud infrastructure
- Experience with RAG, agent orchestration, and LLM evaluation techniques
- A high tolerance for ambiguity and shifting priorities
🌊Comfort with discomfort is essential. Timelines will move. Priorities will change. That’s part of building something real .
🏆 Why Exceptional People Say Yes
Top engineers don’t optimise for comfort — they optimise for trajectory.
âś…People choose environments like this because:
- Talent density permanently raises their bar
- Founder access is direct and unfiltered
- One year of learning feels like several elsewhere
- The experience compounds long after they leave
🔥 The Bottom Line
This role is not for everyone — and it’s not meant to be.
But if someone wants to:
- Build real agentic AI systems used at scale
- Own critical infrastructure, not just features
- Learn directly from founders who’ve built and exited before
- Trade short-term intensity for long-term career acceleration
Then this is one of the most compelling Applied AI Engineering opportunities in Europe right now.
👉 A team of 7 engineers is being hired rapidly.
If this reads as intimidating and exciting — that’s usually the right signal.
