Senior AI Automation Engineer

Innovecs; Guarulhos; Híbrido; BRL 120.000 - 150.000; Tempo integral

Resumo da oferta

A technology company located in São Paulo, Brazil, seeks an AI Automation Engineer to design and implement automation workflows using low-code platforms and JavaScript. You will create integrations and optimize operations by leveraging large language models and automation methods. Candidates should have at least 3 years of experience in similar roles, solid JavaScript skills, and the ability to communicate effectively in English. This position offers a dynamic work environment focused on innovation and efficiency.

Qualificações

• 3+ years of experience in automation integrations.
• Strong skills in JavaScript for automation logic.
• Experience with REST APIs and webhooks.

Responsabilidades

• Design AI-powered automation workflows.
• Create integrations between systems using APIs.
• Develop data pipelines for multiple data sources.

Conhecimentos

Low-code/no-code automation platforms

JavaScript

LLM APIs

REST APIs

Problem-solving skills

English (Upper-Intermediate level)

Ferramentas

Python

Zapier

n8n

AWS

GCP

Descrição da oferta de emprego

Requirements

• 3+ years of professional experience building integrations, automations, or workflow systems
• Strong proficiency with low-code/no-code automation platforms (n8n, AI for business automation - Tray.ai, Zapier, Make | AI Workflow Automation Software & Tools, or similar)
• Solid JavaScript skills - most automation logic happens in JavaScript nodes and custom functions
• Hands‑on experience with LLM APIs (OpenAI, Anthropic Claude, or similar) and prompt engineering
• Experience working with REST APIs, webhooks, and authentication patterns (OAuth, API keys, JWT)
• Understanding of data transformation and formats (JSON, XML, CSV)
• Ability to read API documentation, debug integration issues, and troubleshoot automation failures
• Experience building event-driven workflows and handling asynchronous processes
• Strong problem-solving skills and ability to translate business requirements into technical solutions
• Self‑motivated, disciplined, and comfortable working independently across time zones
• Great communication skills - ability to explain technical concepts to non-technical stakeholders
• Your English is at least at the Upper-Intermediate level to communicate with our teams
• Preferred Skills/Abilities
• Experience building AI agents or multi-step LLM workflows (LangChain, CrewAI, AutoGen, or custom implementations)
• Python scripting for data processing, API integration, or ETL workflows
• Familiarity with workflow orchestration tools or iPaaS platforms (Temporal, Workato, MuleSoft)
• Understanding of vector databases and semantic search for RAG implementations
• Experience with freight, logistics, or supply chain systems and terminology
• Knowledge of SQL and database queries for data analysis
• Background in operations, RevOps, data engineering, or technical product roles
• Experience measuring and optimizing automation ROI (cost per call, error rates, processing time)
• Experience with cloud platforms (AWS, Azure or GCP) and serverless architectures
• Understanding of microservices architecture and event-driven systems

Responsibilities

• Design and deploy AI-powered automation workflows using low-code platforms and custom JavaScript
• Build intelligent systems that leverage large language models (LLMs) for decision-making, data extraction, and process automation
• Create and maintain integrations between internal systems and third-party platforms using APIs, webhooks, and event-driven architectures
• Develop data pipelines that transform, enrich, and route information across multiple systems and data sources
• Implement prompt engineering strategies and design multi-step LLM orchestration workflows
• Build and optimize automated workflows that eliminate repetitive manual tasks across operations teams
• Monitor automation health, debug failures, and continuously optimize workflows for reliability, performance, and cost-efficiency
• Identify new automation opportunities by collaborating directly with operations, product, and engineering teams
• Document workflows, create runbooks, and establish best practices for scalable AI automation
• Participate in code reviews and contribute to shared automation libraries, frameworks, and templates
• Measure and report on automation performance metrics, including accuracy, latency, cost savings, and operational impact
• Prototype new AI capabilities and experiment with emerging technologies as part of our Technical Innovation Program
• Example Projects & Initiatives To give you a sense of the types of challenges you’ll tackle, here are examples of projects our AI Automation Engineers work on:

• Intelligent Document Processing:

  • Build systems that automatically extract structured data from unstructured documents (PDFs, emails, images)
  • Create validation workflows that use AI to verify data accuracy and flag anomalies for human review
  • Design document classification systems that route different document types to appropriate processing pipelines
  • Implement OCR + LLM workflows that handle handwritten or poorly scanned documents

• AI-Powered Business Process Automation:

  • Develop AI agents that conduct multi-step research and qualification processes autonomously
  • Build conversational systems that handle routine inquiries and escape complex cases appropriately
  • Create intelligent routing and matching systems that optimize business outcomes using historical data and ML models
  • Design automated scheduling and coordination systems that handle complex business logic and constraints

• System Integration & Data Orchestration:

  • Connect internal platforms with external third-party services, handling authentication, rate limiting, and error recovery
  • Build real-time data synchronization pipelines that keep multiple systems consistent
  • Create webhook listeners and event processors that trigger automated workflows based on external events
  • Design data enrichment pipelines that pull information from multiple sources and merge it intelligently

• Operational Intelligence & Monitoring:

  • Build automated alerting and notification systems that detect anomalies and trigger appropriate responses
  • Create dashboards and reporting workflows that aggregate data from multiple sources
  • Develop predictive systems that use historical patterns to forecast operational needs
  • Design automated quality control systems that continuously validate data accuracy across systems

  • AI Innovation & Experimentation:

    • Prototype new AI capabilities using the latest LLM models and techniques
    • Experiment with vector databases, semantic search, and retrieval‑augmented generation (RAG)
    • Build proof-of-concepts that demonstrate the business value of emerging AI technologies
    • Contribute to our Technical Innovation Program (TIP) with novel automation approaches

  • Platform & Infrastructure:

    • Develop reusable automation components, templates, and design patterns
    • Create internal tooling that makes it easier for other teams to build and deploy automations
    • Establish monitoring, logging, and observability standards for automation workflows
    • Build testing frameworks that ensure automation reliability and catch regressions
  • These projects span multiple teams and business functions - you’ll have the opportunity to work on whatever creates the most business value, from carrier operations to customer experience to internal productivity tools.