Empresa: Kstack
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.