Fortive

Compensation

Full Description

Provide technical thought leadership, drive technology direction across anesthesia and ultimately help our teams produce exceptional software that is tightly aligned with business objectives. Work closely with Product Management and cross-functional teams to evaluate, design, and implement AI/ML-powered features, including Generative AI and predictive analytics, across Provation products. Develop and maintain architectural principles, frameworks, and strategies with a strong focus on cloud-native, AI-first solutions that align with business objectives. Drive architectural vision and build consensus across multiple engineering teams, incorporating scalable AI/ML pipelines and GenAI technologies. Identify and promote reusability of code, models, and AI/ML components to accelerate delivery of intelligent features. Lead the design and rapid development of proof-of-concepts (POCs) (based on AI/ML and GenAI, if required) that can be evaluated by beta customers for real-world feedback and iterative validation. Serve as an advocate for Agile methodologies and modern software engineering practices. Research, assess, and apply emerging trends in Generative AI, machine learning, analytics, and cloud computing to drive product innovation. Leverage cloud platforms and MLOps tools to improve time-to-market and operational efficiency of AI/ML features. Ensure architectural compliance with enterprise security, data governance, and model lifecycle standards. Produce and maintain system models, AI architecture diagrams, and solution artifacts that clearly articulate design decisions and data flows. Collaborate in Agile ceremonies including daily standups, estimation, sprint planning, and retrospectives, with an emphasis on AI-driven development. Participate in code and model reviews, mentoring engineering and QA teams in AI/ML design patterns, responsible AI practices, and cloud architecture. Lead prototyping and innovation efforts using GenAI to explore new product capabilities and AI-powered business workflows. Bachelor's degree in computer science, Data Science, or a related technical field preferred; equivalent work experience accepted. 3-5+ years of software architecture experience, including at least 2 years in AI/ML solution architecture, with hands-on experience in Generative AI, ML pipelines, or AI-driven analytics. Strong programming skills in C#, .NET Core, and hands on experience with Python or other ML-oriented languages/frameworks (e.g., TensorFlow, PyTorch). Experience with microservices-driven architecture, including designing, developing, and deploying distributed systems using containers (e.g., Docker), Kubernetes (AKS preferred), and Azure Service Fabric or similar platforms. Experience with both SQL (e.g., Azure SQL Database) and NoSQL (e.g., Cosmos DB), and managing datasets for model training and inference in Azure environments. Proven experience designing and delivering rapid prototypes and POCs, preferably using Azure AI and cloud services, tested with beta customers or internal stakeholders. Deep expertise in Microsoft Azure, including services like Azure Machine Learning, Azure OpenAI, Cognitive Services, Azure Functions, Azure Data Lake, and Azure Synapse Analytics. Proficient in web technologies such as JavaScript, TypeScript, HTML5, and CSS, with the ability to integrate GenAI features into web applications. Familiarity with Azure DevOps, ARM templates, and CI/CD pipelines for deploying cloud-based and AI-powered applications. Strong understanding of cloud security, data governance, and AI model compliance in regulated environments. Demonstrated ability to quickly build and iterate on AI/ML POCs using Azure services, incorporating user feedback for solution refinement. Excellent communication and collaboration skills, capable of aligning AI/ML architectural direction with both technical and business stakeholders. Experience working in Agile environments and supporting rapid iteration cycles tied to real-world customer validation. Familiarity with HIPAA, GDPR, and other data privacy standards, especially as applied to Azure-hosted healthcare applications. Certification in Microsoft Azure Architecture, AI Engineer, or Data Scientist (preferred but not required). Ability to handle confidential and regulated data (including PHI) in accordance with company and legal requirements. Travel may be required (<5%).