🚀 Agentic AI Engineer🚀
✨Series A Fintech Start-Up ✨
đź’ŽEquity you WILL realiseđź’Ž
đź“Ť Manhattan, New York (4 days per week, in-office)
đź’¸ $200k - $300k
🧩 $160k vested over 4 years (annual vesting)
🚨 This is a career-defining role.
This role sits inside one of the fastest-growing Series A Fintech start-ups, building production-grade agentic systems for complex, high-stakes enterprise workflows. The business has scaled at exceptional speed, closed a record-breaking 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
- 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
🧩 What You’ll Actually Be Building
You will own and drive large portions of the AI agent infrastructure, from design through to production deployment.
- 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
🧠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
🏆 Why Exceptional People Say Yes
Top engineers don’t optimise for comfort — they optimise for trajectory.
- 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
Then this is one of the most compelling Applied AI Engineering opportunities globally right now.
If this reads as intimidating and exciting — that’s usually the right signal.
