Forward Deployed Engineer - Private Equity - AI Products(NYC)

Mondrian Alpha; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

Mondrian Alpha is hiring an Forward Deployed Engineer to join a private equity setting in New York. You will work directly with investment professionals, own AI products end-to-end from discovery to daily use, and influence the shaping of an embedded AI function within deals.

You will build tools to draft papers with evidence traces, surface signals from unstructured data, validate models, and automate research across large data sets.

Qualifications

• 3 to 10 years shipping software in production across deployment engineering roles, bank strats desks, AI product companies, or similar.
• Strong Python, SQL, and modern LLM tooling capabilities including RAG, prompt engineering, evals and API integration.
• Sufficient financial literacy to assess AI-generated numbers for plausibility.

Responsibilities

• Build tools that draft IC papers with source attribution and evidence tracking.
• Surface signals from unstructured data: news, market moves, and competitor intelligence.
• Validate financial models, check assumptions, and catch modelling errors before they matter.
• Develop agentic workflows and internal copilots alongside the investment process.
• Automate research across large volumes of unstructured data to benchmark deals and surface risks.

Skills

User interaction

Python

SQL

LLM tooling

Tools

RAG

Prompt engineering

Evals

API integration

Job description

This is one of the first opportunities in private equity to build an embedded AI engineering function from the ground up.

A well-established PE firm is putting engineers directly inside its investment teams, and hiring one of its first Forward Deployed Engineers to work alongside its healthcare investors in New York. Rather than sitting in a separate tech function, you'd work directly with the people making the deals, identify what's slowing them down, and build the AI products that fix it.

You'd own these products end to end, from the first conversation through to daily use. You decide what gets built, ship it, and see investment professionals actually rely on it. It's also a rare route into private equity for an engineer, with real ownership, direct access to senior decision-makers, and the chance to define a function rather than inherit one.

What you'll work on:

• Building tools that draft IC papers with source attribution and evidence tracking
• Surfacing signals from unstructured data: news, market moves, and competitor intelligence
• Validating financial models, checking assumptions, and catching modelling errors before they matter
• Agentic workflows and internal copilots that sit right alongside the investment process
• Automating research across large volumes of unstructured data to benchmark deals and surface risks

What we're looking for:

• 3 to 10 years shipping software in production, whether from a deployment engineering role, a bank strats desk, an applied AI product company, or anywhere you've built customer-facing AI
• Strong Python, SQL, and modern LLM tooling: RAG, prompt engineering, evals, API integration
• Enough financial literacy to know when an AI-generated number looks wrong
• Someone who likes talking to users, moving fast, and operating in ambiguity

Healthcare or life sciences exposure is a plus, and you don't need to have held the FDE title before.