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Artificial Intelligence Engineer

Omnis Partners | New York, New York, United States | Today
$200,000 – $300,000/yr| full-time | hybrid | mid
skills: python, django, fastapi, rag, agent orchestration, llm evaluation, docker, kubernetes, cloud infrastructure, relational databases, redis, task queues, backend engineering, apis, design, deployment, enterprise workflows, ai infrastructure

🚀 Agentic AI Engineer🚀

Series A Fintech Start-Up

💎Equity you WILL realise💎

📍 Manhattan, New York

💸 $200k - $300k depending on level

🧩 $160k equity vested over 4 years

🚨 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 at the end of last year, and is now focused on building an elite engineering team to own the core AI infrastructure end-to-end.

💪 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.

#AIjobs #AIhiring #startup

Benefits

equity · health insurance
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