Senior Conversational AI & LLM Engineer – Intelligent Agents, Digital Channels

Winover Contact Center

LLM Engineer developing conversational agents for Winover's SaaS platforms. Focus on intelligent workflows and modern architectures in digital channels like WhatsApp and Telegram.

Posted 6/9/2026full-timeMogi das Cruzes • 🇧🇷 BrazilSeniorWebsite

Tech Stack

Tools & technologies

PythonReact

About the role

Key responsibilities & impact

Design and develop conversational agents based on LLMs for digital channels.
Create conversational flows and agentic architectures using patterns such as Plan-and-Execute, ReAct (Reasoning + Acting), Self-Reflection / Self-Critique.
Implement multi-agent workflows with task delegation and agent cooperation.
Design, document and optimize structured prompts for different use cases.
Implement strategies for context management and conversational memory.
Develop context builders, enrichment pipelines and token-control mechanisms.
Implement Tool Use (Function Calling) to integrate with external APIs.
Define secure and robust JSON schemas for tool execution.
Handle execution errors and create fallback mechanisms for agents.
Implement Retrieval Augmented Generation (RAG) architectures.
Develop document ingestion pipelines, embedding generation and semantic indexing.
Analyze conversation logs, quality metrics and user feedback.
Monitor metrics such as resolution rate, fallback rate, latency and cost per token.
Build evaluation datasets and automated tests for continuous agent improvement.
Develop Python scripts and pipelines for automation and integrations.

Requirements

What you’ll need

Degree in Software Engineering, Computer Science, Artificial Intelligence, Computational Linguistics or related fields.
Experience developing chatbots or conversational agents on platforms such as Blip, Dialogflow, Twilio, Zenvia or custom frameworks.
Strong experience with Python, including: consuming and integrating with REST APIs; automations and scripting; data manipulation and processing.
Experience with Generative Language Models (LLMs) and their APIs, such as OpenAI (GPT), Anthropic (Claude), Gemini, Mistral or other open-source models.
Practical knowledge of LLM concepts and Prompt Engineering, including: tokens, embeddings, context, temperature, few-shot learning and chain-of-thought.
Experience with code versioning (Git) and API testing tools such as Postman.
Good communication skills, analytical thinking and attention to detail.

Benefits

Comp & perks

Positive Work Environment: We believe a healthy organizational climate is essential for everyone’s well-being. Here you will find colleagues and managers ready to support your development.
Opportunities for Growth: We invest in our employees’ professional growth through training and internal promotions.

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Hard Skills & Tools

PythonREST APIsGenerative Language ModelsPrompt EngineeringTask delegationContext managementRetrieval Augmented GenerationDocument ingestionData manipulationAutomations

Soft Skills

Communication skillsAnalytical thinkingAttention to detail