MLOps Engineer (Python) — AI Platform

Job Description

If you've ever said "the model is fine — the infrastructure is broken"... this one's for you.

AI Infrastructure Engineer (Python)
$150,000 – $180,000 + Performance Bonus
New York City | Hybrid (4 Days Onsite)
$3 Billion Boutique Hedge Fund

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THE OPPORTUNITY
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A $3B+ boutique hedge fund has AI agents running in production. They work. Now they need someone to make them scale, stay up, and run fast under real-world load.

This is not a research role. No Jupyter notebooks. No "we're exploring AI." It's already built — now they need the engineer who owns it.

You'll be the person who keeps production humming, scales what's working, and builds the tooling that makes every data scientist on the team faster.

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WHAT YOU'LL ACTUALLY DO
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Write production-grade Python — services, pipelines, shared libraries, internal tooling
Own containerized deployments end to end — Docker, CI/CD, versioning, runtime management
Keep AI agents running at scale — high availability, performance, resilience under load
Build observability into everything — logging, tracing, monitoring, alerting
Manage cloud infrastructure with Terraform across Azure and GCP
Deploy and maintain workflow orchestration (Prefect)
Troubleshoot production issues across the full stack — app to infra

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YOU'RE THE RIGHT FIT IF...
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3–5 years in Software Engineering, DevOps, or MLOps
Python is your primary language — and you've shipped it in production
Docker and containerized cloud deployments are second nature
You've used Terraform in a real environment, not just tutorials
You think in systems — you debug end to end, not just your layer
CI/CD and Git-based release workflows are part of your daily life
You're genuinely curious about AI infrastructure — not just checking a box

Bonus points for:
Azure (Container Apps, Key Vault, ACR, VNets) | GCP (Cloud Run, GKE, Vertex AI) | Prefect | LangChain | MCP | Langfuse | MLflow | dbt | Snowflake | Multi-cloud

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WHY THIS ROLE IS DIFFERENT
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AI agents are already in production — you're scaling something real, not building a proof of concept
Greenfield tooling mandate — you'll build the shared infrastructure the whole team runs on
Direct impact — the platform you maintain shapes investment decisions at an institutional level
Small, sharp team — real ownership, not a ticket queue
Stable, long-term seat at a fund that has been around and isn't going anywhere
Room to grow deeper into AI/ML concepts alongside the platform

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PLEASE READ BEFORE APPLYING
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Full-time, direct hire / W2 only
US Citizens and Green Card holders only — no visa sponsorship
No C2C, no consulting, no third-party agencies

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This role won't be open long. If this sounds like you — or someone you know — DM me directly.

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