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Artificial Intelligence Engineer

Omnis Partners • Full-time • New York, NY, US • $200k - $350k / year • 1w ago

🚀 Applied AI Engineer 🚀

✨Famous Founders ✨

The AI start-up that WILL succeed - the equity you WILL realise

📍 Manhattan, New York (5 days per week, in-office)

💸 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 .

💪 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.

✅People choose environments like this because: