This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engenheiro MLOps Sênior AWS based in Brazil.
This is a fully remote opportunity for a Senior MLOps Engineer to help build, operate, and evolve machine learning solutions in AWS environments.
You will work closely with Data Science teams to turn models and AI applications into reliable, scalable, production-ready solutions.
The role combines MLOps, cloud architecture, software engineering, automation, and emerging LLM technologies.
You will design and maintain automated pipelines while ensuring the stability, performance, and evolution of cloud-based systems.
You will also contribute to the development of APIs, web applications, and LLM-powered agents that support data and AI initiatives.
The position offers an opportunity to solve complex technical challenges in a collaborative, innovation-driven environment.
If you are proactive, analytical, and passionate about cloud, AI, and automation, this role offers meaningful opportunities to make an impact.
Accountabilities:
- Design, develop, validate, and maintain MLOps pipelines, automating processes and integrating them with AWS services.
- Architect, implement, and continuously evolve cloud-based systems, ensuring technical solutions align with project objectives and scalability requirements.
- Collaborate closely with Data Scientists to operationalize, deploy, monitor, and maintain machine learning models and applications.
- Ensure the stability, maintenance, and continuous improvement of the n8n workflow automation platform.
- Develop and integrate APIs and technical solutions that enable efficient communication between systems and services.
- Design and implement web applications and LLM-based agents to support data science and AI initiatives.
- Investigate and resolve technical incidents and support requests related to MLOps environments.
- Identify opportunities for automation, optimization, reliability, and improved operational efficiency across cloud and AI workflows.
- Contribute to technical decisions and recommend appropriate tools, architectures, and engineering practices.
- Support monitoring, observability, performance, and reliability initiatives across production environments.
Requirements:
- Minimum of 3 years of professional experience working with AWS and MLOps.
- Strong hands-on experience with Python and software development practices.
- Proven experience designing, developing, and integrating APIs.
- Solid knowledge of AWS services, cloud-native practices, and infrastructure architecture.
- Experience designing and maintaining systems in cloud environments.
- Practical understanding of Machine Learning concepts and the operationalization of ML models.
- Analytical and proactive approach to diagnosing and solving complex technical problems.
- Strong ability to collaborate with Data Scientists and other technical stakeholders.
- Experience working independently in a fully remote environment.
- Knowledge of Kubernetes and container orchestration is a strong advantage.
- Familiarity with monitoring and observability tools such as Prometheus, Grafana, Datadog, or similar platforms is desirable.
- Knowledge of FinOps principles and cloud cost management is considered a plus.
- Front-end development knowledge is an additional advantage.
Benefits:
- 100% remote work.
- Medical insurance with Porto Seguro, with coverage options for spouse and children.
- Dental insurance with Porto Seguro.
- Profit Sharing and Results Participation (PLR).
- Childcare assistance.
- Meal and food allowance through Alelo.
- Home office allowance.
- Partnerships with educational institutions, including discounts and incentives for courses and degrees.
- Support and incentives for professional certifications, including cloud certifications in AWS, Azure, GCP, and other technologies.
- Livelo points program.
- TotalPass access with discounted fitness plans for employees and family members.
- Mindself wellness and mindfulness program.
- A collaborative environment focused on professional development, health, and quality of life.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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