Senior Azure Cloud Solution Architect

Overview

Senior Azure Cloud Solution Architect

Location : Brazil / Argentina (Remote)

Long term contract

Job Summary

We are seeking a visionary Automation Senior Cloud Solution Architect to lead the technical design and implementation of this transformative capability. This role is pivotal in architecting a scalable, AI-driven solution that seamlessly integrates advanced data processing, intuitive web interfaces, and intelligent automation.

This position demands a strategic leader who thrives in complexity and is deeply committed to cultivating strong stakeholder relationships. You will play a key role in fostering a culture of innovation and collaboration, guiding cross-functional teams to deliver solutions that drive pricing transparency, operational efficiency, and market competitiveness.

The ideal candidate will bring a unique blend of technical depth and strategic foresight, with a proven track record of leveraging cutting-edge technologies to deliver end-to-end automation at scale. The role will interface with Enterprise Architecture, Business leaders, Senior Leaders and Cyber / Privacy / Legal teams.

Key Responsibilities

• Champion Software Excellence & Talent Development. Promote strong SDLC practices including clean architecture, automated testing, and scalable design. Mentor junior developers through code reviews, technical guidance, and collaborative learning to foster a high-performing engineering culture.
• Lead Automation use cases architecture using technologies like GenAI, API, D&A, etc, working closely with Product Managers, automation engineers and stakeholders across business and DTS, and Enterprise Architecture.
• End-to-End Platform Development. Build and maintain front-end (React, TypeScript, Next.js) and back-end (Python, FastAPI, Node.js) layers that support GenAI workflows and agentic interactions.
• API & Agent Framework Integration. Design robust REST and GraphQL APIs for real-time agent communication, tool execution, and memory handling. Integrate frameworks such as LangChain, LangGraph, CrewAI, and vector databases (Pinecone, FAISS, Chroma, Weaviate).
• ETL & Data Pipeline Architecture. Architect and optimize ETL pipelines for real-time and batch data processing. Ensure seamless data flow between GenAI services, databases, and user interfaces.
• Cloud-Native Deployment & Monitoring. Deploy and scale services using Docker, Kubernetes, and CI / CD pipelines. Apply MLOps best practices for monitoring, versioning, and performance tuning of AI components.
• Cross-Functional Collaboration. Work closely with AI researchers, product managers, and delivery teams to align technical execution with strategic goals. Participate in multi-agent orchestration experiments and rapid prototyping cycles.

Key Qualifications and Experiences

Technical Expertise :

Specialized Skills

Soft Skills and Others

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