Lead ML Engineer: Autonomy & Agentic Workflows

The Walt Disney Company; Buenos Aires; Hybrid; ARS 4,200,000 - 5,400,000; Full time

Job summary

The Walt Disney Company in Buenos Aires is seeking a Lead Machine Learning Engineer to build the agentic workflows for D-Fi, Disney's AI framework for finance processes. You will design and implement a scalable multi-agent orchestration layer, enforce identity and guardrails, and lead prompt engineering standards across the platform.

Collaboration with finance experts and strong emphasis on safe autonomous action are key.

Qualifications

• 7+ years of software or ML engineering with end-to-end ownership.
• Advanced English required and highly proactive.
• Bachelor's in Computer Science, Engineering or related field.
• Hands-on multi-agent/agentic LLM systems in production.
• Strong judgment for when autonomy should stop and escalate.
• Ability to influence engineers on standards without formal authority.
• Curiosity about finance processes: forecasting, variance analysis, approvals.

Responsibilities

• Own the agentic workflow layer and multi-agent orchestration.
• Make agent architecture decisions and handle handoffs/failures.
• Enforce identity context across agent actions and escalations.
• Set prompts and context engineering standards for the team.
• Collaborate with finance domain experts to map processes.
• Design for graceful failure and human-in-the-loop escalation.

Skills

ML Engineering

Python

SQL

Snowflake

Temporal/Airflow

Multi-agent systems

Failure-mode design

Technical leadership

Finance process curiosity

English proficiency

Education

Bachelor's in CS/Engineering

Advanced degree a plus

Tools

LangGraph / AutoGen

OpenAI API

AWS/Azure/GCP

Snowflake

Job description

The Walt Disney Company in Buenos Aires is seeking a Lead Machine Learning Engineer to build the agentic workflows for D-Fi, Disney's AI framework for finance processes. You will design and implement a scalable multi-agent orchestration layer, enforce identity and guardrails, and lead prompt engineering standards across the platform.

Collaboration with finance experts and strong emphasis on safe autonomous action are key.