AI Forward Deployed Engineer

Arlo•New York, NY

3d•$180,000 - $225,000•Hybrid

About The Position

AI Forward Deployed Engineers will embed directly inside the core functions of Arlo's business to rebuild how work gets done. At most insurance companies, teams like underwriting, claims, premium finance, member support, care navigation, and sales operations rely on external vendors and legacy SaaS tools. At Arlo, these systems are built in-house. The role involves working closely with these teams to understand their operations, using AI to automate, augment, and redesign workflows. This includes building AI agents, internal tooling, copilots, decision systems, and operational infrastructure to enable teams to scale beyond traditional headcount. This is not a pure research or traditional software engineering role; it requires spending time within the business, shadowing operators, identifying bottlenecks, mapping workflows, and rapidly deploying systems to eliminate manual work and reduce operational overhead. The ultimate goal is for every team at Arlo to become AI-native.

Requirements

Obsessed with customers and their success.
Driven to achieve real, visible results.
Utilizes feedback to generate new ideas and features.
Shipped full-stack AI and LLM applications.
Proficient in Python, Postgres, and modern AI workflows.
Skilled in handling tradeoffs between speed, safety, power, and reliability.
Builds guardrails into all deployed systems.
Leverages AI-powered developer tools for rapid development.

Responsibilities

Embed within operational teams across the company, including underwriting, claims, premium finance, patient experience, broker operations, and sales engineering, to understand decision-making processes, identify workflow slowdowns, and determine automation opportunities.
Build AI underwriting agents to synthesize risk, summarize cases, and assist decision-making.
Automate claims workflows that currently require manual review and coordination.
Create internal copilots for support and care navigation teams.
Design systems to extract structure and actions from complex healthcare documentation.
Deploy retrieval, memory, and evaluation systems to enhance operational reliability over time.
Replace repetitive back-office workflows with AI-native tooling and agents.
Move quickly, ship directly into production, and iterate closely with end-users, with success measured by operational leverage (faster workflows, fewer manual processes, lower costs, and scalable teams).