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AI Forward Deployed Engineer

  • Source: LinkedIn
  • Alldus
  • $250,000 to $300,000 /yr
  • On-site
  • New York City
  • Full-Time
  • Mid level

Job Description

Overview

This role lives at the intersection of the customer and the central platform codebase: you’ll work directly with PE portfolio companies to scope, build, and ship AI agents against real operational data, as well as build out the core platform. Half forward-deployed engineer, half platform builder.

What You’ll Own

  • Forward Deployment: Embed with customers — PE firms and their portcos — to scope problems, design solutions, and ship AI agents against live operational data.
  • Solution Engineering: Translate messy, real-world workflows into working systems: entity resolution, workflow inference, and agent deployment.
  • Customer Trust: Be the technical face in the room — earn credibility with operators and GPs, run demos, and own outcomes end-to-end.
  • Rapid Prototyping: Stand up POCs and pilots fast using AI-native tooling. •
  • Feedback Loop: Partner with the CTO and product to close the loop between what you do in the field and the central roadmap.

Ideal Background

  • Experience: 5–10 years building production software, ideally with direct customer or stakeholder exposure (forward-deployed, solutions/sales engineering, or founding-team work).
  • AI Nativity: Fluent with modern LLM tooling — coding agents, retrieval, evals, and agent frameworks — and shipping with them daily.
  • Technical Fluency: Strong in Python and/or TypeScript, comfortable across the stack and with data (SQL, ETL, wrangling messy enterprise systems).
  • Customer Instinct: Can sit with a non-technical operator, diagnose the real problem, and translate it into a scoped technical solution.
  • Bias to Ship: Comfortable owning ambiguous, high-stakes deployments end-to-end under time pressure.

Bonus Points

  • Startup DNA: Early hire or founder; comfortable wearing many hats and owning high-impact work endto-end.
  • Data Depth: Experience with entity resolution, data unification, or building on modern warehouses/lakehouses such as Snowflake, Databricks, or BigQuery.

Key Competencies

  • Customer-Obsessed Builder: Equal parts engineer and trusted advisor — motivated by shipping things customers actually use.
  • Intensity & Resourcefulness: Relentless about getting to the right answer; finds a way through when the path isn’t obvious. •
  • High Accountability: Communicates clearly, owns outcomes, and thrives in fast-paced, ambiguous environments.

Skills

  • Python
  • TypeScript
  • microsoft-typescript
  • Snowflake
  • azure-databricks
  • databricks

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