Staff Automation Engineer & AI Engineer
New
BrazilFull-TimeStaff
Salary not disclosed
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Job Details
- Required Skills
- AWSDockerPythonKubernetes
Requirements
- Degree in Computer Science, Engineering, or related technical discipline (or equivalent experience).
- Strong expertise in Python, including production-grade development and architectural design.
- Deep experience with workflow automation platforms (e.g., n8n or similar), including governance and scalable architecture design.
- Hands-on experience building AI orchestration systems using tools such as LangGraph, Langflow, CrewAI, Semantic Kernel, or similar.
- Strong knowledge of API design, integration patterns, and distributed system architecture.
- Advanced AWS experience, including cloud-native architecture for scalable and secure systems.
- Experience with RPA platforms (UiPath, Blue Prism, Automation Anywhere, or Power Automate).
- Strong understanding of containers, Docker, Kubernetes, serverless, and modern deployment models.
- Strong security mindset, including secure coding, data protection, and governance practices.
- Experience with AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) and engineering enablement practices.
- FinOps awareness.
- Proven experience applying AI frameworks in real-world production systems.
Responsibilities
- Define the end-to-end automation operating model, including governance, intake, prioritization, lifecycle management, and support structures.
- Establish technical standards for observability, auditability, incident management, logging, metrics, and production support of critical automations.
- Design and govern AI and LLMOps practices, including prompt/version control, evaluation frameworks, human-in-the-loop patterns, and responsible AI usage.
- Architect reusable automation components, frameworks, connectors, and reference architectures to standardize and accelerate delivery.
- Lead the design and governance of workflow automation platforms (e.g., n8n), RPA solutions, and AI orchestration systems.
- Define integration standards, API contracts, and system interoperability patterns for scalable automation ecosystems.
- Drive cloud architecture decisions on AWS, ensuring scalability, resilience, security, and cost efficiency across automation workloads.
- Establish security, compliance, and risk management standards embedded into all automation and AI workflows.
- Stay hands-on in complex engineering work, including coding, architecture design, debugging, code reviews, and production support.
- Mentor engineers and promote best practices in automation, AI engineering, and secure software development.
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