Arquiteto Sênior | Agentic AI / Machine Learning

KSTACK; São Paulo; Hybrid; BRL 350,000 - 550,000; Full time

Job summary

KSTACK in Brazil is seeking a Senior Architect to lead Agentic AI and Machine Learning initiatives within Azure Machine Learning. You will design scalable ML solutions, govern architectures, and guide cross-functional teams in hybrid work settings.

The role emphasizes MLOps, model governance, data pipelines, and collaboration with data scientists and engineers to deliver production-ready services with strong performance and compliance.

Qualifications

• Extensive hands-on experience architecting ML solutions with Azure Machine Learning.
• Strong knowledge of Python-based ML ecosystems and cloud-native design patterns.
• Experience with distributed systems or Distributed Order Management domains.
• Hybrid work experience in cross-functional Agile environments.

Responsibilities

• Define end-to-end ML solution architectures using Azure ML that scale with business growth.
• Design data pipelines and feature engineering workflows for training and inference datasets.
• Implement MLOps practices in Azure ML for training, deployment, and monitoring.
• Collaborate with Data Scientists, Data Engineers, and apps teams to productionize models.
• Establish model governance standards, versioning, and audit readiness.
• Document reference architectures and reusable blueprints for future projects.

Skills

Machine Learning

Azure

Azure Machine Learning

Python-based ML ecosystems

Hybrid work experience

Tools

Python

Azure Machine Learning

Job description

We are seeking a highly experienced Senior Architect specializing in Agentic AI and Machine Learning to design, guide, and govern scalable Machine Learning solutions using Azure Machine Learning.

Position Overview

Experience: 12-16 years
Work Model: Hybrid
Shift: Day shift
Required Skills: Machine Learning, Azure, Azure Machine Learning
Preferred Domain Experience: Distributed Order Management
Technology: Custom Service
Role Classification: Senior Architect - Technology [45TC00]
Required Certification: Microsoft Certified: Azure AI Engineer Associate or an equivalent cloud certification focused on Machine Learning

Key Responsibilities

• Define end-to-end Machine Learning solution architectures aligned with enterprise standards, leveraging Azure Machine Learning services to deliver reliable, reusable components that can scale with business growth.
• Design data pipelines and feature engineering workflows to prepare high-quality training and inference datasets, integrating structured and unstructured data from multiple enterprise systems.
• Implement robust MLOps practices in Azure Machine Learning, automating model training, validation, deployment, and monitoring to ensure consistent performance and rapid iteration cycles.
• Partner closely with Data Scientists, Data Engineers, and application teams to transition experimental models into secure, efficient, production-ready services that meet latency, accuracy, and resiliency requirements.
• Establish standards and guardrails for model governance, including versioning, audit readiness, ethical-use considerations, and ongoing risk assessment across Machine Learning solutions.
• Optimize compute, storage, and networking choices within Azure Machine Learning to balance performance, reliability, sustainability, and cost efficiency for batch and real-time workloads.
• Guide teams on best practices for experimentation, feature utilization, model explainability, and drift detection to improve trust and transparency for business stakeholders.
• Document reference architectures, technical decision records, and reusable blueprints that enable project teams to accelerate new Machine Learning initiatives while maintaining architectural consistency.
• Partner with Product Owners and Business Analysts to translate strategic objectives into Machine Learning roadmaps that prioritize high-value use cases and measurable business outcomes.
• Evaluate emerging Azure Machine Learning capabilities and open-source frameworks, conduct structured proofs of concept, and recommend adoption paths that provide clear long-term value.
• Coordinate the integration of Machine Learning services with enterprise applications, APIs, and event streams to create seamless intelligent workflows that improve user and customer experiences.
• Assess non-functional requirements, including security, privacy, scalability, observability, and operational resiliency, and define repeatable standards for Machine Learning solutions.
• Mentor senior technical contributors in areas such as model industrialization, cloud-native design, and data-driven solution architecture to improve overall delivery quality across programs.

Qualifications

• Extensive hands-on experience architecting and delivering Machine Learning solutions using Azure Machine Learning, including data preparation, model training, deployment, and monitoring.
• Strong knowledge of Python-based Machine Learning ecosystems and cloud-native design patterns, with the ability to define architectures that support both experimentation and reliable production services.
• Experience with distributed systems or Distributed Order Management domains, designing intelligent solutions capable of handling large-scale order flows, inventory signals, and fulfillment constraints.
• Deep understanding of data modeling, data quality management, and feature engineering to ensure models are built on reliable and trusted data foundations.
• Proven experience working in hybrid work models and cross-functional Agile environments, effectively coordinating with geographically distributed stakeholders.
• Strong ability to analyze complex business problems, identify Machine Learning opportunities, and clearly communicate architectural recommendations to both technical and non-technical audiences.

Required Certification

Microsoft Certified: Azure AI Engineer Associate or an equivalent cloud certification focused on Machine Learning.