Forward Deployed AI Engineer (Applied AI)

TL;DR

Forward Deployed AI Engineer (Applied AI): Design, build, and ship production-grade AI agents and workflows for critical institutions with an accent on LLM tooling, customer-facing implementation, and measurable business value. Focus on identifying high-leverage use cases, deploying reliable systems with real users and data, and turning customer learnings into reusable product capabilities.

Location: On-site in New York City, United States

Salary: $150,000–$400,000 base salary plus equity.

Company

An applied AI company helping healthcare, manufacturing, energy, and other critical institutions adopt frontier technology through engineering, product, research, and agentic workflow tooling.

What you will do

• Collaborate with customer executives, operators, and technical teams to define AI strategies and transformation roadmaps.
• Identify and prioritize AI use cases connected to measurable business outcomes.
• Rapidly design, build, deploy, and iterate production AI agents and workflows.
• Work directly with end users and customer stakeholders to deliver practical improvements.
• Contribute customer-derived features, patterns, and abstractions to the Mosaic product.

Requirements

• Hands-on experience with LLM tooling such as LangGraph, Mastra, or Agents SDK.
• Experience building and deploying production LLM-powered systems, including tool use, RAG pipelines, multi-step agents, or human-in-the-loop workflows.
• Strong technical foundations in Python or TypeScript.
• Experience with cloud deployment on AWS, GCP, or Azure and DevOps tooling.
• Ability to work with high ownership, speed, ambiguity, and direct customer collaboration.
• Availability for on-site work in New York City is required.

Nice to have

• Prior startup experience.
• Founding engineer experience.

Culture & Benefits

• Base compensation includes a $150,000–$400,000 salary range and equity.
• Work centers on ambitious, high-impact problems in critical institutions.
• Autonomy, ownership, rapid decision-making, and direct communication are expected.
• Work is outcome-focused rather than based on monitored hours.
• Culture combines execution intensity, candid feedback, customer obsession, and kindness.