Applied AI Engineer Remote 84K-120K USD

LATAM Applied AI Engineer Santiago del Estero Province Argentina Remote Avg $84K$120K USD

Role Overview

A fast-growing AI startup focused on the entertainment industry and creator economy is seeking a LATAM-based Applied AI Engineer to help scale and improve the reliability of production-grade multi-agent systems.

This is not a generic full-stack engineering role. The team is specifically looking for someone with real-world experience operating debugging and improving non-deterministic LLM systems under production traffic.

The ideal candidate understands how AI agents fail in real environments and has experience building evaluation pipelines observability systems scoring frameworks and feedback loops that improve reliability at scale.

This role works closely with the technical co-founder on architecture decisions involving agent reliability human-in-the-loop escalation systems multi-channel routing and production evaluation workflows.

About the Company

The company builds AI agents for the global entertainment industry and creator economy. Its platform is already being used in private beta by professionals associated with Netflix WME UTA Live Nation and other major entertainment organizations.

The founding and technical teams include leaders from companies such as NVIDIA Intuit HubSpot Warner Music Group Robinhood and Hebbia AI. The company has raised significant early-stage funding and is rapidly scaling its AI infrastructure capabilities.

Key Responsibilities

AI Agent Reliability & Evaluation Systems

Instrument and monitor AI agent systems using observability tooling

Build and maintain evaluation datasets from real production traffic

Develop scoring pipelines focused on quality robustness and reliability

Improve human-in-the-loop escalation systems and failure handling

Analyze LLM behavior under real-world production conditions

Create feedback loops connecting evaluations prompts and architecture changes

Backend & Infrastructure Engineering

Build and maintain backend systems using Python technologies

Operate end-to-end across development testing deployment and production sustainment

Support multi-agent orchestration systems and workflow infrastructure

Improve reliability across scheduling messaging and communication agents

Participate in architecture discussions involving AI reliability and scalability

Observability & Optimization

Work with logging metrics and monitoring systems

Evaluate and improve AI-assisted workflows and production tooling

Support experimentation around DSPy DPO and future optimization systems

Help scale evaluation infrastructure as the platform grows

Requirements

Real production experience working with non-deterministic LLM systems

Experience building or operating evaluation pipelines for AI systems

Strong Python backend development experience

Experience with FastAPI Django Celery or similar backend technologies

Familiarity with LangGraph or similar agent orchestration frameworks

Experience with observability platforms such as Langfuse Grafana Loki or equivalent

Ability to independently own projects from development through deployment and production support

Strong written communication and fluent English skills

Ability to work effectively in async remote environments

Preferred Qualifications

DSPy DPO or LLM optimization experience

Multi-agent systems and tool-use orchestration experience

Exposure to production multi-model stacks including GPT-4o Claude or Whisper

Previous startup or high-growth technology company experience

Background at strong LATAM technology organizations or YC-backed startups

Strong product-oriented engineering mindset

Compensation & Benefits

Avg Salary: $84000$120000 USD

Fully Remote LATAM Opportunity

High ownership and technical autonomy

Direct collaboration with experienced founders and AI leaders

Opportunity to help shape production AI reliability systems at an early-stage company

Ideal Candidate

Deeply technical AI engineer focused on reliability and production systems

Comfortable working independently in fast-moving startup environments

Strong systems thinker with practical engineering judgment

Obsessed with improving LLM reliability and agent performance

Product-minded engineer who understands operational tradeoffs

Excited about the future of AI agents within the creator economy and entertainment industry