Lead Software Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Software Engineer based in Brazil.

Lead the development of innovative software products and AI-powered solutions that transform business operations and deliver exceptional digital experiences. In this role, you will define technical direction, guide architecture decisions, and lead projects from early discovery through production delivery. You will help establish an AI-native engineering culture, leveraging advanced coding tools, intelligent agents, and scalable cloud technologies. Working closely with senior engineering and product leaders, you will translate complex business challenges into practical, high-impact solutions. You will also mentor engineers, strengthen development standards, and ensure that technical decisions balance quality, cost, risk, and speed. This opportunity is suited to a hands‑on technical leader who thrives in a fast-moving environment and is passionate about turning ambitious AI strategies into reliable products.

Accountabilities:

As Lead Software Engineer, you will own technical execution for a team or product while helping shape the broader engineering strategy. You will combine architectural leadership, hands‑on development, cross-functional collaboration, and team mentorship to deliver measurable business outcomes. Your responsibilities will include:

• Lead AI Initiatives End to End: Define and maintain the architecture roadmap for your team or product, transforming ambiguous business objectives into clear technical plans and production-ready software.

• Shape AI Architecture: Partner with senior engineering leaders to develop and implement approaches involving AWS Bedrock, retrieval-augmented generation (RAG), agentic architectures, evaluation pipelines, and production safeguards.

• Establish AI-Native Development Practices: Design and implement agentic coding workflows using tools such as Claude Code, including reusable skills, engineering standards, and review processes that ensure AI-generated code meets production requirements.

• Drive Technical Decisions: Evaluate architectural options, make informed trade‑offs, retire outdated designs, and establish scalable, maintainable solutions aligned with product and business priorities.

• Mentor and Develop Engineers: Raise engineering standards through hands‑on leadership, pairing, code reviews, constructive feedback, and reusable technical guidelines.

• Connect Engineering with Business Needs: Collaborate with teams across departments to understand operational challenges and identify opportunities where AI agents and automation can reduce manual work and improve efficiency.

• Manage Cost, Risk, and Delivery: Communicate technical trade‑offs and risks in terms of timelines, costs, and business impact, helping stakeholders make informed decisions.

• Lead Design and Code Reviews: Guide system design, review implementation quality, and evaluate build‑versus‑buy decisions to support effective technical execution.

• Translate Strategy into Results: Work closely with AI, product operations, and product leadership to prioritize initiatives, stay connected to end users, and keep engineering efforts focused on measurable outcomes.

• Support Product Innovation: Contribute to software platforms and AI-enabled tools that support complex brand experiences, event operations, guest registration, hospitality, and asset management.

Requirements:

The ideal candidate is an experienced software engineer with strong technical judgment, a track record of delivering products end to end, and the leadership skills to guide teams through complex engineering challenges. They should be comfortable applying AI technologies in production environments and making decisions that balance innovation with reliability. Key qualifications include:

• Extensive hands‑on software engineering experience, including ownership of products or major initiatives from concept through deployment.

• Proven technical leadership experience, including setting architectural direction, making design decisions, and guiding engineering teams.

• Strong understanding of AI-powered software development, including AI coding assistants, agentic workflows, and the evaluation of AI-generated code.

• Familiarity with cloud-based AI services such as AWS Bedrock and concepts such as RAG, agentic patterns, evaluation pipelines, and production guardrails.

• Experience designing scalable software architectures and making informed decisions about system design, technology selection, and build‑versus‑buy trade‑offs.

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