Desenvolvedor(a) Sênior Full Stack - AI Engineering

Accountabilities:

• Build end-to-end product features using Java on the backend and React on the frontend, taking ownership across the full development lifecycle.
• Implement integrations with external scheduling APIs, including failure handling, retry mechanisms, consistency, and reliable data exchange.
• Design and develop conversational orchestration, defining how LLMs classify requests, extract information, generate responses, and determine when conversations should be transferred to human support.
• Model and evolve data persistence using both relational and non-relational databases, selecting appropriate approaches according to product and technical requirements.
• Develop messaging and asynchronous processing for operations that need to run independently of the active conversation.
• Write automated tests, participate actively in code reviews, and contribute to maintaining high engineering standards.
• Participate in architecture discussions and contribute technical reasoning to important product and engineering decisions.
• Investigate, troubleshoot, and resolve issues in production environments while maintaining system reliability.
• Use AI-assisted development tools thoughtfully and critically, reviewing generated code and outputs rigorously before integrating them into the product.
• Share technical context, collaborate closely with a small squad, and support less experienced team members through knowledge sharing and mentoring.

Requirements:

• Solid professional experience in software development with a track record of delivering and maintaining production applications.
• Strong hands-on expertise with Java backend development and React frontend development, with the autonomy to work effectively across both areas.
• Experience with Docker and containerization, plus familiarity with deployment environments such as Azure.
• Strong knowledge of relational databases, including data modeling, querying, and performance optimization.
• Experience with non-relational databases and a clear understanding of when NoSQL approaches are appropriate.
• Daily experience with AI-assisted software development using tools such as Claude Code, GitHub Copilot, Cursor, or equivalent solutions, combined with sound judgment about where AI accelerates development and where human review is essential.
• Deep knowledge of applied AI and LLM application engineering, including prompt design, structured outputs, RAG, guardrails, and quality evaluation.
• Experience consuming and integrating third-party APIs.
• Strong autonomy, with the ability to unblock yourself while recognizing when collaboration or support is needed.
• A strong quality mindset balanced with pragmatism and the ability to deliver without unnecessary perfectionism.
• Excellent collaboration and communication skills, particularly within a small, highly interactive engineering team.
• Genuine curiosity about applying AI to real-world products and customer experiences.
• Experience with conversational platforms such as Chatwoot, Rasa, Botpress, Dialogflow, or similar tools is a plus.
• Knowledge of the WhatsApp Business API (WABA), including templates, the 24-hour messaging window, and BSP integrations, is advantageous.
• Experience with Azure OpenAI or equivalent technologies is a plus.
• Experience working with healthcare products, sensitive data, and LGPD requirements is advantageous.
• Previous experience building products in an MVP or early-stage environment is a plus.

Benefits:

• Fully remote work model within Brazil.
• Full-time employment opportunity.
• Opportunity to work on a new conversational AI product with direct impact on patient and healthcare experiences.
• Significant technical autonomy and ownership within an early-stage product environment.
• Hands-on exposure to modern LLM application engineering and applied AI technologies.
• Daily use of AI-assisted software development practices and tools.
• Opportunity to work across Java, React, Azure, databases, APIs, messaging, and conversational AI.
• Close collaboration within a small engineering squad where technical contributions and ideas are highly visible.
• Opportunities for knowledge sharing, mentoring, and continuous professional development.
• Inclusive environment that values diversity, respect, ethics, collaboration, and continuous learning.
• Access to learning and development initiatives, technical communities, training programs, and educational partnerships.