Jobs → Engineering → Agentic AI Engineer

About the Role We are seeking an experienced Agentic AI Engineer with strong hands-on expertise in Microsoft Azure AI Foundry to design, develop, deploy, and manage enterprise-grade Agentic AI solutions. Key Responsibilities • Provision, configure, and manage Azure cloud environments for enterprise AI workloads, including Azure AI Foundry, Azure OpenAI, Azure AI Search, networking, identity, and key management. • Design, develop, and deploy intelligent AI agents using Azure AI Foundry and related Azure AI services. • Build and manage agentic workflows, LLM-based applications, orchestration, and enterprise AI integrations. • Develop CI/CD pipelines, Infrastructure as Code (IaC), and LLMOps processes to automate the deployment, monitoring, scaling, and management of AI agents. • Implement enterprise security, compliance, and Responsible AI controls, including Private Endpoints, Role-Based Access Control (RBAC), identity management, and content safety. • Integrate AI agents and applications with enterprise systems and the Databricks platform to support real-world business processes. Requirements • Azure AI Foundry – Hands-on experience building and deploying enterprise AI agents. • Agentic AI Development – Experience designing and implementing autonomous AI agents and agentic workflows. • Azure OpenAI – Strong experience with LLM integration and enterprise GenAI applications. • Azure AI Search – Experience with enterprise search, retrieval, and knowledge integration. • Azure Cloud Infrastructure – Provisioning and managing Azure environments for AI workloads. • LLMOps / MLOps – Building deployment, monitoring, and operational pipelines for AI applications. • CI/CD & Infrastructure as Code – Automating AI solution deployment and infrastructure management. • Azure Security – Private Endpoints, RBAC, identity management, networking, and key management. • Databricks Integration – Experience integrating AI solutions with Databricks and enterprise data platforms. • Monitoring & Optimization – AI usage, cost, latency, performance, and adoption monitoring. • Communication Skills – Excellent communication, stakeholder management, and presentation skills.