About This Role
<p>We are seeking a highly skilled Senior Agentic AI Engineer to design, develop, and deploy production-grade agentic AI systems on Azure cloud infrastructure. The ideal candidate will have extensive experience building autonomous AI agents, deploying complex AI solutions to production, and implementing robust CI/CD pipelines.</p><p></p><p><b> Key Responsibilities</b></p><p>- Design and develop sophisticated agentic AI systems capable of autonomous decision-making and task execution</p><p>- Architect and implement production-grade AI solutions using Azure services (Azure Functions, Azure OpenAI, Azure Cognitive Services, etc.)</p><p>- Build and maintain CI/CD pipelines using Azure DevOps and/or GitHub Actions for automated testing and deployment</p><p>- Develop scalable data processing workflows using Azure Databricks and Apache Spark</p><p>- Implement comprehensive testing strategies for AI applications including unit tests, integration tests, and performance testing</p><p>- Optimize AI agent performance, reliability, and cost-efficiency in production environments</p><p>- Design and implement monitoring, logging, and observability solutions for AI systems</p><p>- Mentor junior engineers and lead technical discussions on AI architecture and best practices</p><p>- Collaborate with cross-functional teams to integrate AI agents into existing systems</p><p>- Implement security best practices including managed identities, Key Vault integration, and RBAC</p><p></p><p></p><p><b> Required Skills & Qualifications</b></p><p><b>Technical Expertise:</b></p><p>- 5 to 8 years of experience in AI/ML engineering with at least 2+ years focused on agentic AI or autonomous systems</p><p>- Expert-level proficiency in Python and advanced knowledge of SQL</p><p>- Deep understanding of Azure cloud services (Azure Functions, Azure OpenAI, Azure ML, App Services, Storage, Key Vault)</p><p>- Extensive hands-on experience with Azure Databricks for large-scale data processing and ML workflows</p><p>- Proven track record of deploying and maintaining AI systems in production environments</p><p>- Strong experience building CI/CD pipelines using Azure DevOps and/or GitHub Actions</p><p>- Proficiency in containerization technologies (Docker, Kubernetes/AKS)</p><p></p><p><b>AI/ML Knowledge:</b></p><p>- Strong foundation in Machine Learning, Natural Language Processing, and Deep Learning</p><p>- Experience with large language models (LLMs) and prompt engineering</p><p>- Knowledge of multi-agent systems</p><p>- Understanding of RAG (Retrieval-Augmented Generation) architectures</p><p>- Experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Transformers)</p><p></p><p><b>Problem-Solving & Quality:</b></p><p>- Exceptional analytical and problem-solving skills with ability to debug complex distributed systems</p><p>- Experience designing and implementing comprehensive test suites for AI applications</p><p>- Strong understanding of software engineering best practices (clean code, design patterns, SOLID principles)</p><p>- Experience with monitoring tools (Application Insights, Log Analytics, Grafana)</p><p></p><p><b> Preferred Qualifications</b></p><p>- Azure certifications (Azure AI Engineer Associate, Azure Solutions Architect)</p><p>- Experience with microservices architecture</p><p>- Knowledge of MLOps practices and tools (MLflow, Azure ML Pipelines)</p><p>- Experience with vector databases and semantic search</p>