This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an Engenheiro(a) de IA Sênior — Python e Agentes (LangGraph) based in Brazil.
As a Senior AI Engineer specializing in Python and agentic systems, you will design, maintain, and evolve AI agents that automate real-world workflows for healthcare clinics and medical practices. You will work at the intersection of large language models (LLMs), backend engineering, and intelligent automation, building agents that interact with patients and clinic teams through WhatsApp. Your role will involve developing business-specific tools, integrating APIs, and ensuring reliable execution across complex, multistep workflows. You will also establish robust evaluation and monitoring practices to optimize agent quality, response times, and operating costs. Working closely with product stakeholders and serving as a technical reference for AI engineering, you will help transform emerging AI capabilities into dependable, production-ready solutions. This is an opportunity to take ownership of innovative projects in a fast-moving, fully remote environment where technical excellence, pragmatism, and continuous learning are highly valued.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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Accountabilities:
Maintain and evolve AI agents: Develop, maintain, and improve existing agentic systems built with LangChain and LangGraph, contributing to both architectural decisions and implementation.
Build business-specific agent tools: Design and implement tools that enable AI agents to execute real operational tasks for healthcare clinics, integrating these capabilities with internal APIs and external services.
Develop WhatsApp integrations: Connect AI agents to WhatsApp-based communication channels, supporting automated interactions with patients and clinic teams through reliable messaging workflows.
Integrate large language models: Implement production-ready LLM capabilities, including tool calling, structured outputs, and retrieval-augmented generation (RAG), to support accurate and context-aware agent behavior.
Ensure workflow reliability: Design robust execution flows with persistent state across conversations, asynchronous processing, queues, retries, and appropriate error handling.
Monitor agent performance: Measure and optimize response quality, latency, and operational costs using evaluations, structured logs, and performance metrics.
Implement testing and quality standards: Develop automated tests and maintain sound software engineering practices to ensure reliability, maintainability, and predictable behavior in production.
Strengthen application security: Identify and address risks associated with LLM-powered applications, including prompt injection, sensitive data exposure, and privacy requirements.
Collaborate with product teams: Work closely with Product to plan technical deliverables, assess feasibility, prioritize improvements, and translate business needs into effective AI solutions.
Provide technical leadership: Serve as a technical reference for AI engineering, share knowledge, support architectural decisions, and mentor colleagues when needed.
Drive continuous improvement: Identify technical bottlenecks, propose pragmatic solutions, and balance delivery speed with code quality and long-term system reliability.
Requirements:
Python development: Strong experience developing and maintaining production applications in Python, particularly with FastAPI and Pydantic.
AI agent frameworks: Practical experience with LangChain and LangGraph, or another agent framework, combined with a willingness to work extensively with LangGraph.
Production LLM integration: Demonstrated experience integrating large language models into real applications, including tool calling, structured outputs, and retrieval-augmented generation (RAG).
Database expertise: Experience working with relational databases such as PostgreSQL or MySQL.
Software engineering fundamentals: Knowledge of automated testing with Pytest, Clean Architecture, and best practices for building maintainable, testable, and scalable applications.
Asynchronous processing: Experience implementing queues, webhooks, messaging systems, or other asynchronous processing mechanisms.
Problem-solving and ownership: A proactive mindset, strong accountability, and the ability to investigate and resolve problems beyond the immediate scope of assigned coding tasks.
Collaboration and communication: Ability to work effectively with product and engineering colleagues, communicate technical decisions clearly, and contribute to shared goals.
Learning and adaptability: Humility to teach, learn, ask for help, and adapt to evolving technologies and practices in the rapidly changing AI landscape.
Pragmatic decision-making: Ability to balance speed, quality, reliability, and maintainability when delivering AI-powered solutions.
LLM evaluation (preferred): Experience evaluating AI outputs and using observability or evaluation tools such as Langfuse or LangSmith.
Messaging integrations (preferred): Familiarity with the WhatsApp Cloud API or official Business Solution Providers (BSPs).
Cloud and infrastructure (preferred): Experience with Docker and AWS services, particularly ECS/Fargate, SQS, or Amazon Bedrock.
AI security and privacy (preferred): Knowledge of prompt injection prevention, sensitive data protection, and compliance with Brazil's General Data Protection Law (LGPD).
Technical leadership (preferred): Previous experience mentoring developers, guiding technical decisions, or serving as a technical lead.
Healthcare technology (preferred): Familiarity with healthcare software, clinical workflows, or applications designed for medical practices.
Benefits:
Competitive compensation: Market-aligned remuneration under a service provider (contractor) arrangement.
Fully remote work: Work from home with no regular office attendance required.
Birthday leave: A dedicated day off to celebrate your birthday.
Well-being benefits: Access to Wellhub for fitness and wellness activities.
Paid annual break: Annual paid recess to support rest and work-life balance.
Collaborative work environment: A relaxed, supportive atmosphere that encourages teamwork, knowledge sharing, and continuous learning.
Professional growth: The opportunity to take ownership of AI engineering initiatives, expand your expertise in agentic systems, and contribute to the evolution of production AI applications.
Meaningful impact: Help develop intelligent automation solutions that improve daily operations for healthcare professionals and their patients.
Working schedule: Availability during standard business hours, Monday through Friday.
