Define and lead enterprise AI architecture standards, frameworks, and best practices
Design scalable AI platforms supporting Generative AI, Agentic AI, Machine Learning, and advanced analytics
Establish enterprise governance for AI security, compliance, model lifecycle management, and responsible AI adoption
Partner, collaborate and influence senior leadership to identify high-value AI use cases aligned with business priorities and operational efficiency goals
Lead the end-to-end design and deployment of enterprise AI solutions and intelligent automation initiatives
Architect and implement AI-powered copilots, knowledge assistants, and workflow automation solutions
Integrate AI capabilities into enterprise applications including Microsoft Dynamics 365, SAP S/4HANA, Salesforce, Service Platforms, and custom applications
Design scalable APIs, microservices, and AI orchestration frameworks
Lead implementation of enterprise GenAI solutions leveraging platforms such as OpenAI, Anthropic Claude, Google Gemini, Microsoft Copilot Studio, and Azure AI Services
Build secure enterprise AI integrations with internal data platforms and business systems
Evaluate and optimize LLM performance, cost, governance, and scalability
Collaborate with data engineering teams to establish scalable AI/ML pipelines and data architectures
Design enterprise-grade MLOps and LLMOps capabilities including CI/CD, monitoring, observability, and model governance
Ensure reliability, scalability, security, and operational readiness of AI platforms
Support cloud-native AI deployments across Azure, AWS, and Google Cloud
Serve as technical lead and mentor for AI engineers, developers, and solution architects
Partner with business stakeholders across Manufacturing, Sales, Operations, Finance, and Supply Chain to translate business requirements into AI-enabled solutions
Drive vendor evaluations, proof-of-concepts, and strategic partnerships related to AI technologies
Communicate technical concepts effectively to both technical and executive audiences
Requirements
Bachelor’s or master’s degree in computer science, Artificial Intelligence, Engineering, Data Science, or related discipline
Advanced degree preferred
8+ years of experience in enterprise software engineering, solution architecture, AI/ML engineering, or related technical leadership roles
3+ years of hands-on experience designing and deploying Generative AI / LLM-based enterprise solutions
Experience leading enterprise-scale AI transformation initiatives in global organizations
Strong experience with cloud-native architectures and enterprise integration platforms
Strong proficiency in Python and modern AI/ML frameworks
Experience with OpenAI, Anthropic Claude, Google Gemini, Microsoft Copilot Studio, LangChain, Semantic Kernel, or equivalent AI ecosystems
Experience with vector databases, RAG architectures, AI orchestration frameworks, and prompt engineering
Experience with TensorFlow, PyTorch, Scikit-learn, or similar frameworks
Strong understanding of enterprise API integration, microservices, and distributed architectures
Experience with Docker, Kubernetes, CI/CD pipelines, and DevOps practices
Familiarity with enterprise security and AI governance requirements
Experience integrating AI solutions with SAP S/4HANA, Microsoft Dynamics 365, Power Platform, or similar enterprise platforms
Experience with data engineering technologies including SQL, Spark, Databricks, or equivalent platforms is preferred
Industry experience in Renewable Energy, Manufacturing, Industrial Technology, Utilities, Energy Storage, Global Supply Chain Operations preferred.