Senior AI Engineer 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.

Key Responsibilities - Design and develop sophisticated agentic AI systems capable of autonomous decision-making and task execution - Architect and implement production-grade AI solutions using Azure services (Azure Functions, Azure OpenAI, Azure Cognitive Services, etc.) - Build and maintain CI/CD pipelines using Azure DevOps and/or GitHub Actions for automated testing and deployment - Develop scalable data processing workflows using Azure Databricks and Apache Spark - Implement comprehensive testing strategies for AI applications including unit tests, integration tests, and performance testing - Optimize AI agent performance, reliability, and cost-efficiency in production environments - Design and implement monitoring, logging, and observability solutions for AI systems - Mentor junior engineers and lead technical discussions on AI architecture and best practices - Collaborate with cross-functional teams to integrate AI agents into existing systems - Implement security best practices including managed identities, Key Vault integration, and RBAC Required Skills &

Qualifications Technical Expertise





- 5 to 8 years of experience in AI/ML engineering with at least 2 years focused on agentic AI or autonomous systems - Expert-level proficiency in Python and advanced knowledge of SQL - Deep understanding of Azure cloud services (Azure Functions, Azure OpenAI, Azure ML, App Services, Storage, Key Vault) - Extensive hands-on experience with Azure Databricks for large-scale data processing and ML workflows - Proven track record of deploying and maintaining AI systems in production environments - Solid experience building CI/CD pipelines using Azure DevOps and/or GitHub Actions - Proficiency in containerization technologies (Docker, Kubernetes/AKS) AI/ML Knowledge:
- Strong foundation in Machine Learning, Natural Language Processing, and Deep Learning - Experience with large language models (LLMs) and prompt engineering - Knowledge of multi-agent systems - Understanding of RAG (Retrieval-Augmented Generation) architectures - Experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Transformers) Problem-Solving & Quality:
- Exceptional analytical and problem-solving skills with ability to debug complex distributed systems - Experience designing and implementing comprehensive test suites for AI applications - Strong understanding of software engineering best practices (clean code, design patterns, SOLID principles) - Experience with monitoring tools (Application Insights, Log Analytics, Grafana) Preferred Qualifications - Azure certifications (Azure AI Engineer Associate, Azure Solutions Architect) - Experience with microservices architecture - Knowledge of MLOps practices and tools (MLflow, Azure ML Pipelines) - Experience with vector databases and semantic search Experience Level Senior Level

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