About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engenheiro de Software AI-Native (Domínio em Python) based in Brazil.
Responsibilities
- Develop software using an AI-native approach, orchestrating agents and LLMs from clear specifications while maintaining full technical responsibility for the final outcome.
- Lead Spec-Driven Development, translating business and technical requirements into executable specifications, implementation plans, and clear acceptance criteria.
- Manage progressive AI autonomy according to risk and context maturity, determining when autonomous generation is appropriate and when human intervention or deeper validation is required.
- Participate in augmented Pull Request reviews, evaluating not only syntax and implementation but also intent, acceptance criteria, architectural decisions, functional impact, and AI-generated code.
- Build and maintain reusable knowledge and context assets, including skills, engineering patterns, architectural decisions, connectors, and MCP integrations.
- Apply sound software architecture and engineering practices to deliver clean, maintainable, testable solutions across monolithic and distributed systems.
- Develop automated tests and observability practices, including mechanisms to monitor the quality, reliability, and cost of AI-generated outputs.
- Identify opportunities to reduce rework and technical debt while maintaining a sustainable development pace.
- Collaborate with Product, Engineering, and other multidisciplinary teams through agile practices such as code reviews, pair programming, and mob programming.
- Share knowledge, contribute to technical discussions, and continuously improve the team's AI-native engineering practices.
Requirements
- At least 3 years of professional software development experience, with strong proficiency in Python and the ability to work across other technologies with support from AI tools. Full-stack experience is valued.
- Strong understanding of Spec-Driven Development, including the ability to write unambiguous specifications, break requirements into verifiable plans, and establish acceptance criteria for both humans and AI agents.
- Experience with context engineering for LLMs, including instructions, constraints, examples, tool/MCP selection, and context-window management.
- Practical experience using generative AI and agentic development tools, with sound judgment, critical thinking, and systematic human validation.
- Ability to critically review and improve code written by AI or other developers with the same rigor applied to personally authored code.
- Strong programming fundamentals and ability to produce clean, organized, maintainable, and testable code using object-oriented programming and/or sound software design principles.
- Experience with automated testing, including unit and/or integration testing.
- Proficiency with Git and collaborative development through Pull Requests.
- Experience with SQL databases and fundamental data modeling concepts.
- Familiarity with agile methodologies such as Scrum, Kanban, or XP.
- Strong written communication and specification skills, with the ability to clearly define requirements, technical decisions, and trade-offs.
- Critical thinking and healthy skepticism toward automated solutions, particularly AI-generated outputs.
- Autonomy, ownership, adaptability, and comfort operating in ambiguous and rapidly changing environments.
- Collaborative mindset, strong communication skills, and genuine interest in the success of both the product and the team.
Nice to have
- Practical experience with AI agent orchestration, MCPs, and connectors, including tool composition and AI-driven workflow automation.
- Experience evaluating and observing AI outputs, including quality measurement, regression detection, and token-cost monitoring.
- Knowledge of model-agnostic architectures and AI evaluation practices.
- Experience with distributed architectures, microservices, messaging, asynchronous or parallel processing, and queues.
- Experience with CI/CD, automated builds, and release processes.
- Knowledge of cloud and container technologies such as Docker, Kubernetes, GCP, or Azure DevOps.
- Experience with GenAI frameworks such as LlamaIndex or LangChain, as well as RAG, Tools, and MCP development.
- Experience with Streamlit, Pandas, or low-code automation platforms such as n8n.
- Experience automating processes involving SAP HANA.
- Familiarity with data-intensive applications and scalable AI-driven solutions.
Conditions
- Remote work, offering flexibility and autonomy in your working environment.
- Opportunity to work on AI-native software development and emerging generative AI technologies.
- Exposure to advanced practices involving LLMs, AI agents, MCPs, automation, and context engineering.
- Collaborative environment focused on innovation and continuous learning.