Applied AI Engineer

Applied AI Engineer | Confidential Client | NYC (In Office)

About the Company

My client is building an AI operating system for engineering services firms. Civil, MEP, and environmental engineers run a $350B industry on manual workflows, disconnected documents, and spreadsheet chaos. My client replaces that with intelligent automation and connected data across the full project lifecycle.

They are backed by Tier 1 VCs, raised $5.5M in October 2025, and secured Q2 funding at 4× their prior valuation. The company has reached $1M ARR pre-Series A and is tracking toward a Series A in April. The team is currently 8 people and scaling to 12–15 this quarter.

The Role

My client is hiring 2 Applied AI Engineers to build production-grade LLM systems embedded directly in critical infrastructure workflows.

You will:

• Design and ship LLM and RAG systems end to end

• Build structured data pipelines using Pydantic and modern validation frameworks

• Work with vector databases and optimize retrieval quality

• Integrate foundation model APIs and evaluate tradeoffs across providers

• Deploy scalable AI systems into real enterprise environments

Ideal Background

• 2–6 years building production ML or AI systems

• Deep familiarity with LLM ecosystems and agent architectures

• Experience with RAG, embeddings, and retrieval optimization

• Strong Python engineering discipline

• Comfortable operating in a high-velocity, in-office environment

Comp: $175K to $300K base + 10% bonus + 0.3% to 0.75% equity

Location: NYC, in office

The current team includes alumni from Uber, AWS, Citadel, Stanford, Columbia, MIT, BCG, Scale AI, TikTok, and former founders.

Applied AI Engineer | Confidential Client | NYC (In Office)