Veear
Summary:
Join our Global IT Organization as we shape the future through digital, data, and AI. We are seeking a strategic and hands-on Lead Applied AI Engineer to guide the development and delivery of innovative AI solutions that align with enterprise goals. This high-impact role will lead the design and operationalization of AI models and intelligent agents using Microsoft Azure AI services (and other hyperscalers), large and small language models (LLMs and SLMs), multi-modal LLMs, RAG, and modern development frameworks. The engineer will drive scalable AI and Agentic AI implementations that generate enterprise insights, enhance productivity, and accelerate innovation across our global operations.
Responsibilities:
Lead the design, development, and deployment of scalable AI/ML and Agentic AI solutions that align with enterprise strategy and deliver measurable business impact. Guide cross-functional teams through complex AI initiatives, ensuring alignment with business objectives and technical feasibility. rchitect and operationalize advanced AI models-including LLMs, SLMs, multi-modal models, and traditional ML-using Python and cloud-native platforms such as Azure AI. Build and integrate intelligent agents using frameworks like LangChain and Semantic Kernel into enterprise platforms, driving automation and insight generation. pply MLOps best practices to ensure robust, secure, and compliant deployment pipelines using Azure Machine Learning and Azure DevOps. Serve as a technical advisor to business stakeholders, translating strategic goals into actionable AI solutions and roadmaps. Mentor junior engineers and contribute to the development of AI governance, standards, and best practices across the organization. Evaluate and implement emerging GenAI tools and frameworks, fostering innovation and continuous improvement in our AI capabilities. Ensure AI systems adhere to privacy, security, and regulatory standards including PHI, PII, GDPR, and HIPAA. Collaborate with global teams and enterprise systems (e.g., Power BI, Microsoft Fabric, SAP Datasphere) to integrate AI solutions that enhance decision-making and operational efficiency. Essential Functions of the Role:
Lead collaboration across global, cross-functional teams using modern communication and development tools (e.g., Microsoft Teams, Azure DevOps, GitHub, SharePoint), ensuring alignment and execution of strategic AI initiatives. ct as a thought leader in AI innovation, proactively integrating insights from cutting-edge research, industry trends, and emerging technologies to shape our AI strategy. Mentor and guide junior engineers and peers, fostering technical growth and promoting best practices in AI development and deployment. Navigate ambiguity with confidence, making informed decisions and driving innovative solutions that address complex business challenges. Champion the use of cloud-native platforms and collaborative development environments to prototype, iterate, and deliver enterprise-grade AI solutions. Represent us in internal and external forums as a subject matter expert in AI, contributing to the company's reputation for innovation and excellence. Travel domestically and internationally as needed to support strategic workshops, stakeholder engagement, and project delivery. Requirements:
8-12 minimum overall experience is required Experience in MedTech, medical devices, or regulated healthcare technology is strongly preferred, especially in roles requiring compliance with data privacy and security standards (e.g., GDPR, HIPAA). Experience leading complex AI/ML initiatives across multiple functions, with a proven ability to guide teams, influence strategy, and deliver enterprise-scale solutions Experience driving innovation,and contributing to the development of functional or cross-functional strategies. Bachelor's degree in computer science, Information Systems, Engineering, or related field. Master's degree preferred. One or more of the following is recommended but not required: Azure AI Engineer Associate, Azure Data Scientist Associate, AWS Certified Machine Learning, GCP Cloud Professional Machine Learning Engineer Specialized Skills/Technical Knowledge:
8 years of experience delivering production-ready AI/ML applications, with demonstrated leadership in cross-functional project environments. dvanced proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, TensorFlow), with expertise in building and optimizing AI models. Deep experience with Azure AI/ML tools, including Azure ML, Azure OpenAI, and Azure DevOps; familiarity with other hyperscaler platforms is a plus. Proven ability to design and implement intelligent agents using frameworks such as LangChain, Semantic Kernel, or similar. Expertise in building ML pipelines, integrating APIs, and working with vector databases and retrieval-augmented generation (RAG). Strong understanding of MLOps, containerization (Docker), and CI/CD practices in cloud environments. Knowledge of data governance, privacy, and regulatory compliance in AI implementations, including GDPR and HIPAA. bility to translate ambiguous business problems into scalable technical solutions through experimentation and strategic planning. Preferred Skills/Knowledge: Familiarity with Microsoft Fabric, OneLake, and Power BI integrations. Experience with SAP data platforms like BW, S/4HANA, or Datasphere. Must be fluent in English, both written and verbally
Responsibilities:
Lead the design, development, and deployment of scalable AI/ML and Agentic AI solutions that align with enterprise strategy and deliver measurable business impact. Guide cross-functional teams through complex AI initiatives, ensuring alignment with business objectives and technical feasibility. rchitect and operationalize advanced AI models-including LLMs, SLMs, multi-modal models, and traditional ML-using Python and cloud-native platforms such as Azure AI. Build and integrate intelligent agents using frameworks like LangChain and Semantic Kernel into enterprise platforms, driving automation and insight generation. pply MLOps best practices to ensure robust, secure, and compliant deployment pipelines using Azure Machine Learning and Azure DevOps. Serve as a technical advisor to business stakeholders, translating strategic goals into actionable AI solutions and roadmaps. Mentor junior engineers and contribute to the development of AI governance, standards, and best practices across the organization. Evaluate and implement emerging GenAI tools and frameworks, fostering innovation and continuous improvement in our AI capabilities. Ensure AI systems adhere to privacy, security, and regulatory standards including PHI, PII, GDPR, and HIPAA. Collaborate with global teams and enterprise systems (e.g., Power BI, Microsoft Fabric, SAP Datasphere) to integrate AI solutions that enhance decision-making and operational efficiency. Essential Functions of the Role:
Lead collaboration across global, cross-functional teams using modern communication and development tools (e.g., Microsoft Teams, Azure DevOps, GitHub, SharePoint), ensuring alignment and execution of strategic AI initiatives. ct as a thought leader in AI innovation, proactively integrating insights from cutting-edge research, industry trends, and emerging technologies to shape our AI strategy. Mentor and guide junior engineers and peers, fostering technical growth and promoting best practices in AI development and deployment. Navigate ambiguity with confidence, making informed decisions and driving innovative solutions that address complex business challenges. Champion the use of cloud-native platforms and collaborative development environments to prototype, iterate, and deliver enterprise-grade AI solutions. Represent us in internal and external forums as a subject matter expert in AI, contributing to the company's reputation for innovation and excellence. Travel domestically and internationally as needed to support strategic workshops, stakeholder engagement, and project delivery. Requirements:
8-12 minimum overall experience is required Experience in MedTech, medical devices, or regulated healthcare technology is strongly preferred, especially in roles requiring compliance with data privacy and security standards (e.g., GDPR, HIPAA). Experience leading complex AI/ML initiatives across multiple functions, with a proven ability to guide teams, influence strategy, and deliver enterprise-scale solutions Experience driving innovation,and contributing to the development of functional or cross-functional strategies. Bachelor's degree in computer science, Information Systems, Engineering, or related field. Master's degree preferred. One or more of the following is recommended but not required: Azure AI Engineer Associate, Azure Data Scientist Associate, AWS Certified Machine Learning, GCP Cloud Professional Machine Learning Engineer Specialized Skills/Technical Knowledge:
8 years of experience delivering production-ready AI/ML applications, with demonstrated leadership in cross-functional project environments. dvanced proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, TensorFlow), with expertise in building and optimizing AI models. Deep experience with Azure AI/ML tools, including Azure ML, Azure OpenAI, and Azure DevOps; familiarity with other hyperscaler platforms is a plus. Proven ability to design and implement intelligent agents using frameworks such as LangChain, Semantic Kernel, or similar. Expertise in building ML pipelines, integrating APIs, and working with vector databases and retrieval-augmented generation (RAG). Strong understanding of MLOps, containerization (Docker), and CI/CD practices in cloud environments. Knowledge of data governance, privacy, and regulatory compliance in AI implementations, including GDPR and HIPAA. bility to translate ambiguous business problems into scalable technical solutions through experimentation and strategic planning. Preferred Skills/Knowledge: Familiarity with Microsoft Fabric, OneLake, and Power BI integrations. Experience with SAP data platforms like BW, S/4HANA, or Datasphere. Must be fluent in English, both written and verbally