Source-listed Job

Senior AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer based in Brazil.

Job Remote Source description available
Jobgether Source published Oct 16, 2026 Source retrieved Oct 16, 2026
Source: jobgether (lever) · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
Description from the source The source description is formatted below for discovery. The provider owns the original wording and may change its requirements or close applications.
EmploymentFull-time
Work modeRemote / location-flexible

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer based in Brazil.

Full job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer based in Brazil. We are looking for an experienced AI Engineer to help build and enhance an AI-powered media planning platform. In this role, you will design, develop, and evaluate intelligent agents powered by Large Language Models (LLMs), leveraging Python, AWS Bedrock, and modern AI technologies. You will focus on improving agent reliability, accuracy, security, and performance through robust evaluation frameworks, intelligent workflows, and effective validation mechanisms. Working closely with engineering and product teams, you will contribute to scalable, production-ready AI solutions. This remote opportunity offers the chance to solve complex AI challenges, optimize real-world applications, and make a measurable impact on the quality and efficiency of AI-driven products.

Design, develop, and maintain AI agents and LLM-powered applications using Python and AWS services. Implement and optimize prompt engineering, agent orchestration, structured outputs, and intelligent decision-making workflows. Develop evaluation frameworks to measure agent accuracy, reliability, consistency, and overall performance. Establish performance baselines, automated tests, and regression validation processes to assess changes in agent behavior. Implement guardrails and validation mechanisms to promote safe, accurate, and reliable AI-generated outputs. Build intelligent information retrieval, filtering, ranking, and selection strategies using LLMs. Investigate and resolve issues involving hallucinations, incorrect interpretations, and inconsistent agent responses. Develop end-to-end AI features that integrate LLMs with backend APIs, document processing, and cloud infrastructure. Improve agent observability through execution tracing, session tracking, and production monitoring. Collaborate with engineering and product teams to deliver scalable, production-ready AI solutions. Optimize LLM performance, latency, and operational costs through experimentation and measurable improvements. Requirements: Solid professional experience in AI engineering, machine learning engineering, or software development involving production AI applications. Strong proficiency in Python, including experience developing APIs, integrations, and automated tests. Hands-on experience building applications powered by Large Language Models (LLMs) and implementing agentic AI workflows. Experience with prompt engineering, LLM orchestration, and structured output generation. Practical experience evaluating LLM outputs, designing testing strategies, and measuring AI application quality. Understanding of LLM limitations, including hallucinations, response variability, and reliability challenges. Experience with AWS services such as Bedrock, Lambda, S3, CloudWatch, or similar cloud technologies. Strong knowledge of software engineering best practices, CI/CD, and cloud-based application development. Strong analytical, troubleshooting, and problem-solving skills, particularly when investigating complex agent behavior. Advanced or fluent English communication skills, both written and verbal, to collaborate effectively in a remote environment. Benefits: Health and dental insurance. Meal and food allowances. Childcare assistance. Extended paternity leave. Gym, fitness, and wellness partnerships through platforms such as Wellhub (Gympass) and TotalPass. Profit Sharing and Results Participation (PLR). Life insurance. Access to a continuous learning platform. Discount club membership. Online resources supporting physical, mental, and overall well-being. Pregnancy and responsible parenting courses. Partnerships with online learning platforms. Access to a language-learning platform. Remote work arrangement. Additional benefits and employee support initiatives.

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