Líder Técnico - Arquiteto (Sistemas Internos RH)

Architecture and technical quality:

• Define and sustain architecture decisions for internal systems, integrations, automations, and lakehouse;

• Establish engineering standards for the team: observability, security, maintainability, and documentation;

• Conduct code reviews with criteria, acting as a trainer and mentor for the team, not as a bottleneck;

• Get into the code when necessary: unblock obstacles, validate approaches, and create prototypes.

Technical leadership with AI:

• Define the team's AI strategy: identify where it adds value, where human judgment is indispensable, and how to measure success;

• Leverage AI as an internal development tool: code generation, assisted review, and automation of repetitive tasks;

• Be the reference for best practices in AI use with responsibility and governance, without compromising quality.

Product and business:

• Collaborate with product leadership on defining and designing solutions and effort estimates;

• Translate technical impact into clear roadmap prioritization decisions;

• Communicate technical decisions and risks clearly to different audiences: team, management, and HR stakeholders.

✨ What makes our eyes light up:

We seek people who live our essence and share our purpose: we transform businesses to grow and prosper through technology.

If you put the customer at the center, have a collaborative spirit and focus on what matters, always questioning, learning, and evolving, you already have what we need. We value those who get their hands dirty and take responsibility!

🤩 We expect you to have:

We seek someone who masters the concepts and knows the trade-offs of agent orchestration, asynchronous messaging, and polyglot persistence.

Stacks:

• Backend and services: Python (FastAPI) and TypeScript for microservices and asynchronous workers;

• AI and agents: Mastery of RAG architectures (chunking, embedding, and quality evaluation), familiarity with LLMs (Gemini, etc), experience with frameworks and agent creation patterns. Plus: LangGraph;

• Data: PostgreSQL (relational) and know modeling for different access patterns. Plus: ClickHouse for analytics and lakehouse;

• Infrastructure and Architecture: concepts and practice with Event-Driven, cache, authentication (OAuth2/OIDC), containers, CI/CD pipelines, and observability best practices;

• Frontend: Next.js and Tailwind.

Technical Leadership:

Previous experience acting as Tech Lead, Lead Engineer, or main technical reference in squads, guiding architecture decisions and team evolution.

Deeply Technical: Solid practical experience in building data systems, automations, and complex integrations. Real experience with observability and applied security, not just theoretical.

High Appetite for AI: You have used it, made mistakes, and learned. You have a formed opinion on where AI solves real problems and how to implement it efficiently in day-to-day operations.

Focus on results: Result-oriented, not process-oriented. Works well in contexts of high autonomy and end-to-end responsibility.

Communication: Ability to discuss complex technical trade-offs with non-technical people without losing the depth of the argument.