Tech Lead – AI Engineering

• Drive platform architecture decisions and document the rationale behind them
• Technically lead the squad by defining standards, conducting code reviews, and ensuring delivery quality and momentum
• Write code and build alongside the team
• Define tools and practices for AI-assisted development, including output review and usage boundaries
• Serve as the technical liaison with an external integration partner, anticipating and managing dependency risks
• Define the strategy for containerization, deployment, observability, and infrastructure as code in Azure
• Translate technical constraints into product decisions with the Product Owner and design team, and vice versa
• Develop the team through mentoring, pairing, and context sharing

• Proven experience in software development, with hands-on experience leading technical squads
• Full-stack experience with Java on the backend and React on the frontend
• Experience with Docker and containerization
• Experience deploying and operating applications on Azure
• In-depth knowledge of relational databases, including modeling, performance, and migrations
• Knowledge of non-relational databases and the ability to justify when to use each type
• Experience with asynchronous processing using RabbitMQ, SQS, SNS, or Kafka
• Daily use of Claude Code, Copilot, Cursor, or equivalent tools for AI-assisted development
• Sound judgment regarding where AI tools accelerate development and where they hinder it
• Experience integrating third-party APIs
• Knowledge of designing an anti-corruption layer for unstable contracts
• Mature communication skills to confidently support technical decisions in front of clients
• Autonomy and a strong sense of ownership
• Comfortable working with ambiguity and evolving requirements
• Ability to say no and present alternatives
• Pragmatism in choosing solutions appropriate to the timeline without compromising the future
• Nice to have: Experience with healthcare projects involving sensitive data and Brazil’s LGPD; MVP-stage products; legacy products and monoliths; Azure and AWS

• Autonomy, collaboration, and continuous innovation
• Active participation in technical and architectural decisions
• Strategic projects with a real impact on the business
• Professional development through mentoring, pairing, and context sharing
• Remote work