Join as a Software Engineer to build AI full-stack solutionsand shape an engineering culture that values autonomy, creativity, and technical excellence. 🚀
🌟 What do we offer?
A central role in the team that defines the next products, not just maintains the existing ones
End-to-end ownership of the agentic AI layer on top of what Labs ships
AI-assisted development as a first-class practice, Claude Code, Cursor, Copilot, with the autonomy to exercise real engineering judgment
Modern, multi-cloud stack: MongoDB + SQL, Azure + AWS
Real influence over architecture, technical standards, and engineering culture beyond your immediate team
A high-bar technical environment where your architectural decisions impact multiple teams and products
🧑🏻💻 Responsibilities:
Set architectural direction for products emerging from Labs, from prototype to production
Design and build production-grade agentic workflows: retrieval, tool use, multi-step planning, human-in-the-loop checkpoints, and safety guardrails
Be the senior technical voice in architectural decisions that span multiple teams
Establish technical standards and engineering practices that extend across the organization
Make significant individual contributions to the SaaS product across Azure and AWS
Collaborate with product, design, and engineering across the full SDLC
Mentor and guide engineers and actively influence engineering culture
Ensure performance, quality, and responsiveness of customer-facing applications and the agentic systems built on top of them
Implement and maintain modern automated testing practices, including evals for AI components
Contribute to modernization and consolidation of legacy surfaces as integration touch points emerge
🤝 If you have:
8+ years of professional software development experience, with 3+ years in senior, lead, or principal roles
Deep code fluency: ability to pick up an unfamiliar codebase in any mainstream language and form a defensible opinion in days, not weeks, language is a tool, not an identity
Strong working command of both Azure and AWS and the tradeoffs across container orchestration, serverless, messaging, identity, and managed data stores
Kubernetes in production
Solid command of both SQL and NoSQL systems
Demonstrable AI engineering chops: has shipped LLM-powered features to production; comfortable with retrieval, embeddings, tool calling, structured outputs, and cost/latency tradeoffs
Has designed agentic workflows end-to-end: planning, tool use, evaluation, failure-mode analysis, human-in-the-loop; can articulate when an agent is the right answer and when a deterministic pipeline is
Proven track record of leading architectural initiatives and influencing decisions across teams
Strong technical leadership and mentoring experience
Solid grasp of SOLID, DRY, KISS, YAGNI, and TDD; applies them when warranted
Comfortable ramping into the current stack: C#/.NET backend, Node.js/TypeScript and Vue.js frontend, and into whatever Labs ships next
Advanced English
🦾 It’s a plus:
Working familiarity with Model Context Protocol (MCP), agent frameworks, and eval frameworks
Experience deploying inference workloads on Azure (AI Foundry / Azure OpenAI) and/or AWS (Bedrock, SageMaker)
Experience with Autodesk products and APIs (AutoCAD, Revit, Fabrication, BIM 360 Docs, Forge / APS)
Construction, MEP, or manufacturing domain knowledge
Experience leading large-scale system migrations or architectural transformations
Familiarity with modern serverless technologies on either cloud
Track record of establishing technical standards across engineering organizations
Understanding of event-driven architectures and message-based integration
This call is made within the framework of Law 19.691 on the Promotion of Employment for Persons with Disabilities, including individuals registered in the National Registry of Persons with Disabilities of the Ministry of Social Development
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