Define and drive the AI automation strategy aligned with business objectives and digital transformation initiatives
Design endtoend AI and intelligent automation architectures leveraging LLMs Agentic AI RPA workflow orchestration and cloudnative services
Architect multiagent systems AI copilots conversational solutions and autonomous workflows
Design and implement RAG Vector Database Knowledge Graph and semantic search solutions
Lead integration of AI solutions with enterprise applications APIs databases and thirdparty platforms
Establish AI governance security compliance Responsible AI and model monitoring frameworks
Collaborate with business engineering data science and product teams to identify and prioritize AI automation opportunities
Define AI solution standards architecture patterns reusable components and best practices
Provide technical leadership architecture reviews mentoring and guidance to development teams
Evaluate emerging AI technologies and drive continuous innovation across the organization
Establish and manage MCP server ecosystems ADO Playwright Test JIRA SQL and other enterprise platforms to enable seamless integration orchestration and utilization of GenAILLM capabilities across the organization
Evaluate benchmark and select the most suitable LLMs and AI models based on business requirements use cases performance scalability security and cost considerations
Required Skills Experience
12 years of experience in software engineering solution architecture automation or AI technologies
Robust expertise in Generative AI LLMs Prompt Engineering Agentic AI and AI orchestration frameworks
Experience with Azure AI Foundry Azure OpenAI or similar AI platforms
Handson experience with LangChain LangGraph Semantic Kernel AutoGen CrewAI or equivalent frameworks
Strong knowledge of Python APIs microservices cloudnative architecture and containers
Experience with RPA platforms such as Power Automate UiPath Automation Anywhere or Blue Prism
Expertise in Vector Databases RAG architecture embeddings and enterprise search
Understanding of MLOps LLMOps model deployment monitoring and AI lifecycle management
Strong stakeholder management consulting and communication skills
Handson expertise in designing deploying and managing MCP Model Context Protocol server architectures with a strong understanding of MCP components integration patterns security controls and enterprisescale implementations
Expertise in Responsible AI governance and compliance ensuring AI solutions are ethical secure transparent fair and aligned with enterprise policies and regulatory requirements