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São Paulo, São Paulo, Brasil
Remote only
At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.
With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.
We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.
We are seeking a talented and experienced AI Solutions Data Developer to join the Digital Supply Chain Analytics team. This professional will play a key role in designing, building, deploying, and maintaining AI-enabled business applications, contributing to the digital transformation of our client’s supply chain in the consumer goods sector.
The AI Solutions Engineer will work closely with the Data Scientist and Data Analyst to translate business requirements into scalable applications, databases, workflows, and user-facing tools. The ideal candidate is a hands-on builder who can quickly develop MVPs, harden solutions for production use, and deploy applications in containerized environments.
Application Development:
Design and develop internal applications that support supply chain, logistics, manufacturing, planning, procurement, and operations.
Create user interfaces for data management, workflow execution, AI-assisted recommendations, reporting and analysis, and operational decision support.
Develop APIs and backend services that support business processes.
AI Solution Implementation:
Implement AI and machine learning capabilities as designed by the Data Scientist.
Integrate large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and predictive and optimization models.
Build workflows that operationalize AI insights into business processes.
Database Development & Data Engineering:
Design and maintain PostgreSQL databases, including creating schemas, stored procedures, views, and ETL/ELT pipelines.
Optimize SQL performance and database efficiency.
Support master data management and operational data structures.
Data Integration:
Build and maintain integrations with Google BigQuery, SAP, REST APIs, Microsoft 365, SharePoint, Teams, and third-party SaaS platforms.
Create automated data pipelines and synchronization processes.
Containerization & Deployment:
Package applications using Docker containers and deploy them through platforms like Portainer.
Support environment configuration, secrets management, SSL setup, and container monitoring.
AI-Assisted Development:
Utilize modern development tools like VS Code, GitHub, Codex, Claude, Copilot, and Gemini for rapid prototyping and refining solutions.
Technical Documentation:
Produce and maintain technical specifications, system architecture documentation, data models, API documentation, and deployment guides.
The professional will be expected to:
Build and deploy operational applications.
Create production-ready PostgreSQL data structures.
Develop integrations with BigQuery and enterprise systems.
Deliver functional user interfaces for business teams.
Support the deployment and maintenance of containerized applications.
Assist in AI application implementation and operationalization.
Produce technical documentation for all delivered solutions.
Proficiency in Python
REST API development and PostgreSQL database skills.
Advanced SQL knowledge and query optimization.
Experience with Google BigQuery and data integration frameworks.
Experience integrating LLMs into applications and prompt engineering.
Familiarity with Containerization & Deployment best practices
Good English communication skills - High Intermediate level - B2 CEFR
Experience in supply chain, manufacturing, planning, logistics, inventory management, procurement, and quality systems.
Knowledge of SAP integrations and AI application deployment in operational environments.
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