Agentic AI / Orchestration Lead

Essential Skills: We are seeking an experienced and visionary Agentic AI Orchestration Lead with 10 years of experience in enterprise technology software engineering solution architecture and AI-driven digital transformation. The ideal candidate will lead the design implementation governance and optimization of multi-agent AI ecosystems that enable autonomous business processes intelligent decision-making and scalable enterprise AI adoption Role Descriptions: Strategic LeadershipDefine the enterprise vision roadmap and adoption strategy for Agentic AI and AI orchestration platforms.Establish best practices standards governance frameworks and operating models for AI agents.Drive enterprise-wide AI transformation initiatives and identify high-value automation opportunities.Partner with business and technology leadership to align AI investments with organizational goals.AI Agent Architecture Orchestration Design and implement multi-agent architectures involving planner coordinator executor reviewer and specialist agents.Lead development of orchestration frameworks using technologies such as LangGraph Semantic Kernel AutoGen CrewAI OpenAI Agents or similar platforms.Define agent communication patterns memory management context sharing workflow execution and task delegation strategies.Architect reusable agent services tools APIs and orchestration components.Platform Engineering DeliveryLead development and deployment of production-grade AI agents and autonomous workflows.Establish CICD pipelines testing frameworks and observability mechanisms for AI systems.Ensure scalability resilience security and performance across AI platforms.Guide engineering teams in implementing AI-powered solutions and enterprise integrations.Governance Risk ComplianceEstablish AI governance processes covering security privacy explainability and responsible AI practices.Define monitoring auditing and evaluation frameworks for autonomous agents.Ensure compliance with enterprise architecture standards and regulatory requirements.Mitigate risks related to hallucinations data leakage prompt injection and model drift.Stakeholder Management InnovationCollaborate with business leaders to translate complex requirements into AI-driven solutions.Conduct architecture reviews proof-of-concepts and innovation workshops.Evaluate emerging AI tools models frameworks and orchestration technologies.Promote AI adoption through mentoring training and organizational change management.Team LeadershipLead and mentor AI architects engineers prompt engineers and platform teams.Establish engineering standards development guidelines and quality gates.Drive continuous improvement knowledge sharing and innovation across AI initiatives.Foster a culture of experimentation while maintaining enterprise-grade controls.