Senior Ai Automation Engineer

Innovecs; Teletrabalho; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A technology company in Brazil seeks a skilled individual to build intelligent systems leveraging large language models for decision-making, data extraction, and process automation. The ideal candidate has over three years of experience in automation, familiarity with REST APIs, and strong problem-solving skills. This role includes creating integrations and developing data pipelines across multiple systems. Requirements include proficiency in low-code/no-code platforms and the ability to communicate technical concepts in English.

Qualificações

• 3+ years of professional experience building integrations, automations, or workflow systems.
• Experience with event-driven workflows and asynchronous processes.
• Ability to read API documentation and debug integration issues.

Responsabilidades

• Build systems that leverage large language models for automation.
• Create integrations between internal and third-party platforms.
• Develop data pipelines that transform and route information.

Conhecimentos

Integration building

Low-code/no-code platforms (n8n, Tray.ai, Zapier)

LLM APIs (OpenAI, Anthropic Claude)

REST APIs and webhooks

Data transformation (JSON, XML, CSV)

Problem-solving skills

Communication with non-technical stakeholders

Upper-Intermediate English

Ferramentas

Python

AWS

Azure

GCP

OCR technology

Descrição da oferta de emprego

Qualifications

• 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)
• 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

• 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

• 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 elevate 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
  • 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
• 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.