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Senior Software Engineer AI

Cargill -
São Paulo, SP

Candidate-se Agora

Detalhes da vaga

Há 2 dias

Qualificações

CRM software
Ciência da Computação
Doutorado
Ciência da Computação
Inglês
Banco de Dados
Desenvolvimento de Software
APIs
Inteligência artificial
Debug

Descrição completa da vaga

Want to build a stronger, more sustainable future and cultivate your career? Join Cargill's global team of 160,000 employees who use new technologies, dynamic insights and over 154 years of experience to connect farmers with markets, customers with ingredients, and people and animals with the food they need to thrive.

Job Purpose and Impact

The Senior Professional, Software Engineering job designs, develops and maintains software applications and systems. With minimal supervision, this job collaborates with cross functional teams to define, design and implement new software features to meet user needs and business goals, and upgrade existing software to improve performance and functionality through writing clean, efficient and scalable code and troubleshooting and debugging complex issues. This job also participates in code reviews to maintain high code quality and share knowledge with software engineering team members.
In addition, this role plays a key part in designing and delivering AI‑enabled software solutions, with particular emphasis on Generative AI and intelligent agent‑based systems, applying strong software engineering discipline to AI solutions deployed in production environments.

Key Accountabilities

SOFTWARE DEVELOPMENT: Designs and develops high quality software solutions by writing clean, maintainable and efficient codes.
APPLIED GENERATIVE AI & INTELLIGENT SYSTEMS: Designs, builds and maintains AI‑enabled software solutions with strong emphasis on Generative AI, including large language models (LLMs), AI agents and AI‑driven workflows, ensuring scalability, security, reliability and Responsible AI principles.
AI AGENT DEVELOPMENT: Leads or significantly contributes to the implementation of AI agents and copilots, including reasoning workflows, prompt and orchestration design, tool and function integration, and interaction with enterprise APIs, data sources and platforms.
AUTOMATION: Leads the application of internal software deployment platform, methodologies and tools to automate the deployment process, ensuring smooth and reliable releases.
COLLABORATION: Partners with cross functional team of product managers, designers and different engineers to gather complex requirements and deliver solutions that meet business needs.
TESTING & DEBUGGING: Writes and maintains complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software.
CONTINUOUS IMPROVEMENT: Suggests options for improving the software development and deployment processes, and implements the approved standards to improve efficiency and reliability.
DOCUMENTATION: Builds and maintains comprehensive documentation for complex software applications, deployment processes and system configurations.
TECHNICAL SUPPORT: Provides technical support and troubleshooting for complex issues with deployed applications to ensure minimal downtime and fast resolution.
#LI-RJ2 #LI-Hybrid

Qualifications

Basic fluency in English language and working across multiple time zones with multiple cultures
Experience with Full Stack software development with languages
Proven, hands‑on experience delivering Generative AI solutions, including practical use of large language models (LLMs) in real, production‑grade systems
- Strong, practical experience building AI agents, copilots or intelligent assistants, including orchestration logic, prompt engineering, tool or function calling and system integration
- Demonstrated ability to own AI‑based solutions end‑to‑end, from design and development to deployment, monitoring and continuous improvement
- Ability to work independently and be productive from day one, leveraging prior market experience to solve complex business problems with Generative AI

Preferred Qualifications:

BA/BS in Computer Science, related technical field, or equivalent practical experience
Master’s or PHD in computer science or related field
Demonstrated ability to lead technical teams
Experience with traditional ERP, CRM, and Database Platforms
Experience applying Generative AI in enterprise or regulated environments, balancing innovation with security, compliance and Responsible AI principles
- Experience with AI platforms, agent frameworks or orchestration patterns (e.g., retrieval‑augmented generation, multi‑agent systems)
- Experience partnering with product, data and business teams to translate business challenges into AI‑driven software solutions

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