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IBM

Developer Python/LLM/Machine Learning

IBM

Published 10 May 2026
Brazil
Full Time

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Role Highlights

Languages used

Python

Key skills

Prompt Engineering
API
LLMs
Machine Learning

Tools, Libraries and Frameworks

Rest
Git
IBM

Description

The role involves developing and maintaining conversational agents that operate through both voice and text interfaces. The professional will analyze conversation logs and volumetrics to support ongoing improvements. Responsibilities include translating business requirements into functional conversational features and integrating agents with external systems via APIs. The individual will perform prompt engineering tasks and conduct rigorous testing of agents to evaluate response quality and interaction flows. Collaboration with technical and business teams is essential to ensure the efficiency and user experience of the developed solutions.

Required Qualifications and Skills

The role requires proficiency in Python for developing agents and creating tools and prompts. Candidates must possess knowledge of prompt engineering applied to Large Language Models and experience with automation and RESTful API integration. Familiarity with development tools such as Git for version control and Insomnia for API testing is necessary. Additionally, the individual must be capable of performing functional tests and evaluating the responses generated by language models.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

IBM

Size

305978

Website

ibm.com

HQ

Armonk, New York, US

Public/Private

Public Company

Description

IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.

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